A full-body motion capture gait dataset of 138 able-bodied adults across the life span and 50 stroke survivors

\ua9 2023, The Author(s).This reference dataset contains biomechanical data of 138 able-bodied adults (21–86 years) and 50 stroke survivors walking bare-footed at their preferred speed. It is unique due to its size, and population, including adults across the life-span and over 70 years, as well as stroke survivors. Full-body kinematics (PiG-model), kinetics and muscle activity of 14 back and lower limbs muscles was collected with a Vicon motion capture system, ground-embedded force plates, and a synchronized surface EMG system. The data is reliable to compare within and between groups as the same methodology and infrastructure were used to gather all data. Both source files (C3D) and post-processed ready-to-use stride-normalized kinematics, kinetics and EMG data (MAT-file, Excel file) are available, allowing high flexibility and accessibility of analysis for both researchers and clinicians. These records are valuable to examine ageing, typical and hemiplegic gait, while also offering a wide range of reference data which can be utilized for age-matched controls during normal walking

Music and Hypertonia: Can Music Listening Help Reduce Muscle Tension and Improve Movement Quality?

Although there is a strong consensus that music listening is a common and effective means to induce states of relaxation, little attention has been given to the physical effects of such states and the potential health-related applications. In this article, we investigated whether music listening could induce affective states of relaxation and accelerate the recovery of fatigued muscles, through the analysis of quality of movement. Twenty healthy participants were asked to perform a fatigue induction protocol of the non-dominant arm followed by a resting period and the execution of a drinking task. During recovery periods, all participants were exposed to three experimental conditions: listening to relaxing music; arousing music; and no music. 3D motion capture and surface electromyography were used to record upper limb movements and muscle activity when performing the drinking task before and after the recovery periods. Movement quality was assessed by means of movement smoothness (jerk index) and muscle recovery (motor unit recruitment). Results showed that recovery of movement smoothness in the relaxing music condition was significantly greater (-35%) than in the relaxing music condition (compared to arousing music, -25%, and silence, -16%) which demonstrates that listening to relaxing music speeds up the recovery process of (fatigued) muscles. We discuss our findings in the context of potential applications of music listening for reducing muscle tension in people suffering from hypertonia. </jats:p

PubMeth: a cancer methylation database combining text-mining and expert annotation

Epigenetics, and more specifically DNA methylation is a fast evolving research area. In almost every cancer type, each month new publications confirm the differentiated regulation of specific genes due to methylation and mention the discovery of novel methylation markers. Therefore, it would be extremely useful to have an annotated, reviewed, sorted and summarized overview of all available data. PubMeth is a cancer methylation database that includes genes that are reported to be methylated in various cancer types. A query can be based either on genes (to check in which cancer types the genes are reported as being methylated) or on cancer types (which genes are reported to be methylated in the cancer (sub) types of interest). The database is freely accessible at http://www.pubmeth.org

Genome-wide DNA methylation detection by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison.

Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). Objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples, i.e. 65 glioblastoma and 5 non-tumoral tissues. As MethylCap-seq coverages were limited, we focused on the inherent capacity of the methodology to detect methylated loci rather than a quantitative analysis. MethylCap-seq and HM450 data were dichotomized and performances were compared using a gold standard free Bayesian modelling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. In addition, genome-wide characteristics were compared, revealing that HM450 probes identified substantially fewer regions compared to MethylCap-seq. Although results indicated that the latter method can detect more potentially relevant DNA-methylation, this did not translate into the discovery of more differentially methylated loci between tumours and controls compared to HM450. Our results therefore indicate that both methodologies are complementary, with a higher sensitivity for HM450 and a far larger genome-wide coverage for MethylCap-seq, but also that a more comprehensive character does not automatically imply more significant results in biomarker studies

MGMT Promoter Methylation Cutoff with Safety Margin for Selecting Glioblastoma Patients into Trials Omitting Temozolomide: A Pooled Analysis of Four Clinical Trials.

The methylation status of the O &lt;sup&gt;6&lt;/sup&gt; -methylguanine DNA methyltransferase (MGMT) gene promoter is predictive for benefit from temozolomide in glioblastoma (GBM). A clinically optimized cutoff was sought allowing patient selection for therapy without temozolomide, while avoiding to withhold it from patients who may potentially benefit.Experimental Design: Quantitative MGMT methylation-specific PCR data were obtained for newly diagnosed patients with GBM screened or treated with standard radiotherapy and temozolomide in four randomized trials. The pooled dataset was randomly split into a training and test dataset. The unsupervised cutoff was obtained at a 50% probability to be (un)methylated. ROC analysis identified an optimal cutoff supervised by overall survival (OS). For 4,041 patients valid MGMT results were obtained, whereof 1,725 were randomized. The unsupervised cutoff in the training dataset was 1.27 (log &lt;sub&gt;2&lt;/sub&gt; [1,000 × (MGMT+1)/ACTB]), separating unmethylated and methylated patients. The optimal supervised cutoff for unmethylated patients was -0.28 (AUC = 0.61), classifying "truly unmethylated" (≤-0.28) and "gray zone" patients (&gt;-0.28, ≤1.27), the latter comprising approximately 10% of cases. In contrast, for patients with MGMT methylation (&gt;1.27) more methylation was not related to better outcome. Both methylated and gray zone patients performed significantly better for OS than truly unmethylated patients [HR = 0.35, 95% confidence interval (CI), 0.27-0.45, P &lt; 0.0001; HR = 0.58, 95% CI, 0.43-0.78, P &lt; 0.001], validated in the test dataset. The MGMT assay was highly reproducible upon retesting of 218 paired samples (R &lt;sup&gt;2&lt;/sup&gt; = 0.94). Low MGMT methylation (gray zone) may confer some sensitivity to temozolomide treatment, hence the lower safety margin should be considered for selecting patients with unmethylated GBM into trials omitting temozolomide

Dynamic epigenetic changes to VHL occur with sunitinib in metastatic clear cell renal cancer.

Background: Genetic intratumoral heterogeneity (ITH) hinders biomarker development in metastatic clear cell renal cancer (mccRCC). Epigenetic relative to genetic ITH or the presence of consistent epigenetic changes following targeted therapy in mccRCC have not been evaluated. The aim of this study was to determine methylome/genetic ITH and to evaluate specific epigenetic and genetic changes associated with sunitinib therapy. Patients and methods: Multi-region DNA sampling performed on sequential frozen pairs of primary tumor tissue from 14 metastatic ccRCC patients, in the Upfront Sunitinib (SU011248) Therapy Followed by Surgery in Patients with Metastatic Renal Cancer: a Pilot Phase II Study (SuMR; ClinicalTrials.gov identifier: NCT01024205), at presentation (biopsy) and after 3-cycles of 50mg sunitinib (nephrectomy). Untreated biopsy and nephrectomy samples before and after renal artery ligation were controls. Ion Proton sequencing of 48 key ccRCC genes, and MethylCap-seq DNA methylation analysis was performed, data was analysed using the statistical computing environment R. Results: Unsupervised hierarchical clustering revealed complete methylome clustering of biopsy and three nephrectomy samples for each patient (14/14 patients). For mutational status, untreated biopsy and all treated nephrectomy samples clustered together in 8/13 (61.5%) patients. The only methylation target significantly altered following sunitinib therapy was VHL promoter region 7896829 which was hypermethylated with treatment (FDR=0.077, P<0.001) and consistent for all patients (pre-treatment 50% patients had VHL mutations, 14% patients VHL hypermethylation). Renal artery ligation did not affect this result. No significant differences in driver or private mutation count was found with sunitinib treatment. Conclusions: Demonstration of relative methylome homogeneity and consistent VHL hypermethylation, after sunitinib, may overcome the hurdle of ITH present at other molecular levels for biomarker research.This work was supported by: Chief Scientist Office, Scotland (grant number ETM37 to GDS and DJH); Cancer Research UK (Experimental Cancer Medicine Centre) (to TP, London and DJH, Edinburgh), Medical Research Council (to AL, DJH), Royal College of Surgeons of Edinburgh (to AL), Melville Trust (to AL), Renal Cancer Research Fund (to GDS), Kidney Cancer Scotland (to GDS), the Special Research Fund of Ghent University (grant number 01MR0410 to TDM, GT, WVC, CVN, FVN and DD) and an educational grant from Pfizer (to TP).This is the final version of the article. It first appeared from Impact Journals via https://doi.org/10.18632/oncotarget.830

Chromosome 7 gain and DNA hypermethylation at the HOXA10 locus are associated with expression of a stem cell related HOX-signature in glioblastoma.

BACKGROUND: HOX genes are a family of developmental genes that are expressed neither in the developing forebrain nor in the normal brain. Aberrant expression of a HOX-gene dominated stem-cell signature in glioblastoma has been linked with increased resistance to chemo-radiotherapy and sustained proliferation of glioma initiating cells. Here we describe the epigenetic and genetic alterations and their interactions associated with the expression of this signature in glioblastoma. RESULTS: We observe prominent hypermethylation of the HOXA locus 7p15.2 in glioblastoma in contrast to non-tumoral brain. Hypermethylation is associated with a gain of chromosome 7, a hallmark of glioblastoma, and may compensate for tumor-driven enhanced gene dosage as a rescue mechanism by preventing undue gene expression. We identify the CpG island of the HOXA10 alternative promoter that appears to escape hypermethylation in the HOX-high glioblastoma. An additive effect of gene copy gain at 7p15.2 and DNA methylation at key regulatory CpGs in HOXA10 is significantly associated with HOX-signature expression. Additionally, we show concordance between methylation status and presence of active or inactive chromatin marks in glioblastoma-derived spheres that are HOX-high or HOX-low, respectively. CONCLUSIONS: Based on these findings, we propose co-evolution and interaction between gene copy gain, associated with a gain of chromosome 7, and additional epigenetic alterations as key mechanisms triggering a coordinated, but inappropriate, HOX transcriptional program in glioblastoma

Strategies for validation and testing of DNA methylation biomarkers

DNA methylation is a stable covalent epigenetic modification of primarily CpG dinucleotides that has recently gained considerable attention for its use as a biomarker in different clinical settings, including disease diagnosis, prognosis and therapeutic response prediction. Although the advent of genome-wide DNA methylation profiling in primary disease tissue has provided a manifold resource for biomarker development, only a tiny fraction of DNA methylation-based assays have reached clinical testing. Here, we provide a critical overview of different analytical methods that are suitable for biomarker validation, including general study design considerations, which might help to streamline epigenetic marker development. Furthermore, we highlight some of the recent marker validation studies and established markers that are currently commercially available for assisting in clinical management of different cancers

Identification of Colorectal Cancer Related Genes with mRMR and Shortest Path in Protein-Protein Interaction Network

One of the most important and challenging problems in biomedicine and genomics is how to identify the disease genes. In this study, we developed a computational method to identify colorectal cancer-related genes based on (i) the gene expression profiles, and (ii) the shortest path analysis of functional protein association networks. The former has been used to select differentially expressed genes as disease genes for quite a long time, while the latter has been widely used to study the mechanism of diseases. With the existing protein-protein interaction data from STRING (Search Tool for the Retrieval of Interacting Genes), a weighted functional protein association network was constructed. By means of the mRMR (Maximum Relevance Minimum Redundancy) approach, six genes were identified that can distinguish the colorectal tumors and normal adjacent colonic tissues from their gene expression profiles. Meanwhile, according to the shortest path approach, we further found an additional 35 genes, of which some have been reported to be relevant to colorectal cancer and some are very likely to be relevant to it. Interestingly, the genes we identified from both the gene expression profiles and the functional protein association network have more cancer genes than the genes identified from the gene expression profiles alone. Besides, these genes also had greater functional similarity with the reported colorectal cancer genes than the genes identified from the gene expression profiles alone. All these indicate that our method as presented in this paper is quite promising. The method may become a useful tool, or at least plays a complementary role to the existing method, for identifying colorectal cancer genes. It has not escaped our notice that the method can be applied to identify the genes of other diseases as well

Discovery of DNA methylation markers in cervical cancer using relaxation ranking

<p>Abstract</p> <p>Background</p> <p>To discover cancer specific DNA methylation markers, large-scale screening methods are widely used. The pharmacological unmasking expression microarray approach is an elegant method to enrich for genes that are silenced and re-expressed during functional reversal of DNA methylation upon treatment with demethylation agents. However, such experiments are performed in <it>in vitro </it>(cancer) cell lines, mostly with poor relevance when extrapolating to primary cancers. To overcome this problem, we incorporated data from primary cancer samples in the experimental design. A strategy to combine and rank data from these different data sources is essential to minimize the experimental work in the validation steps.</p> <p>Aim</p> <p>To apply a new relaxation ranking algorithm to enrich DNA methylation markers in cervical cancer.</p> <p>Results</p> <p>The application of a new sorting methodology allowed us to sort high-throughput microarray data from both cervical cancer cell lines and primary cervical cancer samples. The performance of the sorting was analyzed <it>in silico</it>. Pathway and gene ontology analysis was performed on the top-selection and gives a strong indication that the ranking methodology is able to enrich towards genes that might be methylated. Terms like regulation of progression through cell cycle, positive regulation of programmed cell death as well as organ development and embryonic development are overrepresented. Combined with the highly enriched number of imprinted and X-chromosome located genes, and increased prevalence of known methylation markers selected from cervical (the highest-ranking known gene is <it>CCNA1</it>) as well as from other cancer types, the use of the ranking algorithm seems to be powerful in enriching towards methylated genes.</p> <p>Verification of the DNA methylation state of the 10 highest-ranking genes revealed that 7/9 (78%) gene promoters showed DNA methylation in cervical carcinomas. Of these 7 genes, 3 (<it>SST</it>, <it>HTRA3 </it>and <it>NPTX1</it>) are not methylated in normal cervix tissue.</p> <p>Conclusion</p> <p>The application of this new relaxation ranking methodology allowed us to significantly enrich towards methylation genes in cancer. This enrichment is both shown <it>in silico </it>and by experimental validation, and revealed novel methylation markers as proof-of-concept that might be useful in early cancer detection in cervical scrapings.</p