Oxidative Medicine and Cellular Longevity
Volume 2019 (2019), Article ID 9141343, 19 pages
https://doi.org/10.1155/2019/9141343

Research Article

Tocotrienol-Rich Fraction (TRF) Treatment Promotes Proliferation Capacity of Stress-Induced Premature Senescence Myoblasts and Modulates the Renewal of Satellite Cells: Microarray Analysis

Jing Jye Lim,¹ Wan Ngah Wan Zurinah,¹ Vincent Mouly,² and Abdul Karim Norwahidah¹

¹Department of Biochemistry, Faculty of Medicine, Level 17, Preclinical Building, Universiti Kebangsaan Malaysia Medical Centre, Jalan Yaacob Latif, Bandar Tun Razak, 56000 Cheras, Kuala Lumpur, Malaysia
²Thérapie des Maladies du Muscle Strié Institut de Myologie, UM76-UPMC Univ. Paris 6/ U974-Inserm/UMR7215-CNRS, G.H. Pitié-Salpétrière-INSERM, UMRS 974, Institut de Myologie, Université Pierre et Marie Curie, Paris, France

Correspondence should be addressed to Abdul Karim Norwahidah; wahida2609@gmail.com

Received 15 August 2018; Revised 18 October 2018; Accepted 12 November 2018; Published 10 January 2019

Guest Editor: Mohamed M. Abdel-Daim

Copyright © 2019 Jing Jye Lim et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

Human skeletal muscle is a vital organ involved in movement and force generation. It suffers from deterioration in mass, strength, and regenerative capacity in sarcopenia. Skeletal muscle satellite cells are involved in the regeneration process in response to muscle loss. Tocotrienol, an isomer of vitamin E, was reported to have a protective effect on cellular aging. This research is aimed at determining the modulation of tocotrienol-rich fraction (TRF) on the gene expressions of stress-induced premature senescence (SIPS) human skeletal muscle myoblasts (CHQ5B). CHQ5B cells were divided into three groups, i.e., untreated young control, SIPS control (treated with 1 mM hydrogen peroxide), and TRF-posttreated groups (24 hours of 50 μg/mL TRF treatment after SIPS induction). The differential gene expressions were assessed using microarray, GSEA, and KEGG pathway analysis. Results showed that TRF treatment significantly regulated the gene expressions, i.e., p53 (RRM2B, SESN1), ErbB (EREG, SHC1, and SHC3), and FoxO (MSTN, SMAD3) signalling pathways in the SIPS myoblasts compared to the SIPS control group (). TRF treatment modulated the proliferation capacity of SIPS myoblasts through regulation of ErbB (upregulation of expression of EREG, SHC1, and SHC3) and FoxO (downregulation of expression of MSTN and SMAD3) and maintaining the renewal of satellite cells through p53 signalling (upregulation of RRM2B and SESN1), MRF, cell cycle, and Wnt signalling pathways.

1. Introduction

Skeletal muscle is one of the largest organs in the body and contributed to 45-55% of the total body weight [1]. However, skeletal muscle cells are not able to self-replenish as it is a terminally differentiated cells. Thus, skeletal muscle cells require a population of resident adult stem cells, satellite cells for maintenance and repair [2]. Satellite cells are typically mitotically quiescent in resting muscle and will be activated to prepare for cell cycle entry upon stimulation and during muscle injury. A subset of satellite cells will be self-renewed to maintain the satellite cell pool and regenerate a rapidly proliferating transit-amplifying myoblast population.

Regeneration of skeletal muscle cells deteriorated with the aging process. This muscle degeneration process due to aging is termed sarcopenia [3]. Muscle degeneration started with 0.5–1% after 30 years of age and the rate increases as age reaches 65 years [4]. The mechanism of this degeneration is still yet to be deciphered clearly, but it can involve oxidative stress [5]. Muscle atrophy is reported to be stimulated by the PI3K/Akt and NF-κB signalling pathways [6]. Activation of PI3K/Akt signalling regulates the skeletal muscle mass and metabolism in skeletal muscle [7]. On the other hand, inhibition of this signalling pathway would inhibit the FoxO protein and upregulate the atrophy-related gene (atrogin), such as atrogin1/MAFbx1 and MuRF [7, 8]. Braun and Gautel proposed that NF-κB also would involve in the regulation of atrogin and regulate the catabolism and anabolism of muscle protein [7].

Myostatin, a member of the TGF superfamily, was reported as a muscle atrophy inducer by activating the transcription factor SMAD3 which leads to atrogin-1 expression and inhibition of Akt/mTOR signalling and protein synthesis. Moreover, SMAD3 is also involved in the inhibition of peroxisome proliferator-activated receptor-coactivator-1 (PGC1) promoter activity and increased FoxO-mediated signalling [9]. Besides the mentioned FoxO signalling pathway and the expression of atrogin in muscle atrophy, Brack et al. suggested a different signalling pathway in muscle aging, which is the activation of the Wnt/β-catenin signalling pathway that leads to increased muscle fibrosis [10].

Cell senescence is categorised into three major mechanisms, i.e., replicative senescence, oncogene-induced senescence, and stress-induced premature senescence (SIPS) [11]. SIPS cells and replicative senescence cells are similar in molecular action and morphology, such as flat and larger cells, increased activities of senescence-associated β-galactosidase, and cell cycle arrest. However, SIPS was not affected by the length of telomere [12–14]. Hydrogen peroxide (H₂O₂) is a common stress mediator in the SIPS model as it induced the cells to have senescence morphology alike with the replicative senescence cells [11, 12]. Generation of H₂O₂ by the mitochondria or external sources from the cells leads to the damage of mitochondrial components and thus initiated the degeneration process [15].

Since the degeneration of skeletal muscle was closely related to oxidative stress, it was suggested that reestablishment of the redox balance would be beneficial in the amelioration of age-related degeneration in skeletal muscle [16]. Vitamin E, especially tocotrienol, has been widely reported for its antioxidant effects in preventing aging [17–19]. Supplementation of vitamin E (α-tocopherol) together with vitamin C reduced oxidative stress and increased the activities of antioxidant enzymes in the rat skeletal muscle [20].

Various approaches, including pharmacological interventions, nutrition, and physical activities, have been reported to improve the aging conditions of the skeletal muscle. However, to date there is neither supplementation nor intervention that works effectively with minimum side effects [3]. Howard et al. reported that tocopherol promoted the repair of plasma membrane in mouse myocytes [21]. However, these findings were focused on the effects of tocopherol, but not tocotrienol, on skeletal muscle. Previously, our study revealed that the tocotrienol-rich fraction (TRF) has reduced the senescence morphology and improved the proliferation capacity towards stress-induced premature senescence cells [22]. Hence, we would like to identify and elucidate the mechanism involved in the regenerative action of TRF on stress-induced premature skeletal muscle cells.

2. Materials and Methods

2.1. CHQ5B Cell Culture

Human satellite cells were isolated from a biopsy of a 5-day-old infant quadriceps muscle and were kindly provided by Dr. Vincent Mouly from UMRS 787, Institut de Myologie, INSERM, Université Pierre et Marie Curie, Paris, France. Upon isolation, the satellite cells proliferated in culture as myoblasts (known as CHQ5B cells) and were considered to be at 1 mean population doubling (MPD). CHQ5B cells were cultivated in a growth medium at 37°C in a humid atmosphere containing 5% carbon dioxide (CO₂) as described previously [22].

2.2. Treatment Protocols

The Tocotrienol-rich fraction (TRF) was purchased from Sime Darby Sdn. Bhd., Selangor, Malaysia (TRF Gold Tri E 70). TRF consists of α-tocotrienol (26.67%), β-tocotrienol (4.29%), γ-tocotrienol (32.60%), δ-tocotrienol (15.53%), and α-tocopherol (20.81%) [22]. The CHQ5B cells (PD 29 ± 3) were incubated with different treatments, i.e., untreated young control, stress-induced premature senescence (SIPS), and TRF-treated group (SIPS myoblasts posttreated with TRF). Untreated young control cells were cultured without any treatment with ROS inducer or TRF. The SIPS model was established by exposure of CHQ5B cells to the stressor, 1 mM H₂O₂ diluted in growth medium for 30 minutes [22, 23]. In the TRF-treated group, the CHQ5B cells were exposed to the stressor at 1 mM H₂O₂ for 30 minutes followed by incubation in 50 μg/mL TRF (Sime Darby Bioganic Sdn Bhd) for 24 hours [22]. This concentration and duration of TRF treatment were in line with a previous study which showed that SIPS cells posttreated with 24 hours 50 μg/mL TRF were able to increase the proliferation capacity of myoblast cells.

2.3. Total RNA Extraction and Purification

Total RNA from CHQ5B cells in different treatment groups was extracted using TRI Reagent (Molecular Research Center, Cincinnati, OH, USA) according to the manufacturer’s instruction. Polyacryl Carrier (Molecular Research Center) was added in each extraction to precipitate the total RNA. The extracted total RNA pellet was then washed with 75% ethanol and air-dried. The extracted total RNA was dissolved in RNase and DNase-free distilled water and purified by using the RNeasy® Mini Kit (Qiagen, USA) according to the manufacturer’s instruction. Total RNA was then stored at −80°C immediately after extraction and purification. RNA concentration and purity of the extracted RNA were determined by NanoDrop (Thermo Scientific, USA). The quality of RNA was assessed by an Agilent 2100 bioanalyzer (Agilent Technologies, USA). The high quality of RNA, i.e., RNA integrity number (RIN) ranging from 7 to 10 and absorbance ratio of A260 to A280 ranging from 1.5 to 2.1, was utilized for microarray analysis (Figure S01, Supplementary Materials).

2.4. Gene Expression Microarray Profiling

The isolated RNA was amplified and labelled using Affymetrix GeneChip 3’ IVT Express and Affymetrix GeneChip Hybridisation, Wash, and Stain Kit (Affymetrix, Santa Clara, CA, USA) according to the manufacturer’s protocol. The RNA was then hybridised to the Affymetrix GeneChip PrimeView Human Gene Expression Array cartridge, washed, and scanned according to the manufacturer’s protocol. The arrays from three samples each of untreated young control, SIPS control, and TRF-treated cells were scanned and processed by using the AGCC Scan Control (Affymetrix).

2.5. Gene Expression Microarray Data Analysis and Statistics

The raw CEL data files from microarray profiling were imported into the Partek Genomics Suite (v. 6.6; Partek, St. Louis, MO) for analysis, and two-way analysis of variance (2-way ANOVA) was applied with a fold change of 1.5 for the selection of differentially expressed genes at a significance level of . The differentially expressed gene lists were further correlated for their relevant biological function and reaction pathway by analysing the GSEA (Gene Set Enrichment Analysis) and KEGG (Kyoto Encyclopedia of Genes and Genomes) using the Partek Genomic Suite. A significance level ofin the GSEA analysis to identify the significant biological process involved was observed, whereas an enrichment score ofin the KEGG pathway to identify the significant pathway was observed.

2.6. Quantitative Real-Time PCR (qPCR)

The microarray data was validated by using qualitative qPCR. Genes for validation, i.e., GDF15, EREG, RRM2B, SHC3, SHC1, SESN1, MSTN, MYOD1, and SMAD3, were chosen from pathway analysis. By using 2 μL total RNA as template and iScript Reverse Transcription Supermix (Bio-Rad, USA), the cDNA is generated from RNA. The reactions were carried out as follows: priming for 5 minutes at 25°C, then reverse-transcription for 30 minutes at 42°C and inactivation of the reverse-transcription for 5 min at 85°C.

Primer sequences for GDF15, EREG, RRM2B, SHC3, SHC1, SESN1, MSTN, MYOD1, and SMAD3 are shown in Table 1(a). qPCR was carried out by using 1 μL cDNA as template, 1 μL of forward and reverse primers for genes of interest, and SSoAdvanced SYBR Green Supermix (Bio-Rad, USA). All reactions were run in duplicate using Real-Time PCR iQ5 (Bio-Rad, USA). The thermal cycling profiles are presented in Table 1(b). The melt curve analysis of each pair of primers and agarose gel electrophoresis that was performed on the PCR products was used to determine the primer specificity (Figure S02, Supplementary Materials). The gene expression level of each targeted gene was normalized to that of glyceraldehyde 3-phosphate dehydrogenase (GAPDH). It was presented as relative expression value (REV) by using the 2−ΔΔCt method of relative quantification and the following equation:

Table 1: Quantitative real-time PCR: (a) primer sequences and (b) the thermal cycling profile.

(a)

Accession number
Gene
Primer type
Primer sequences (5–3)

NM_001289746
GAPDH
Forward
TTGCCCTCAACGACCACTTT

Reverse
TGGTCCAGGGGTCTTACTCC

NM_004864.2
GDF15
Forward
CAGGACGGTGAATGGCTCTC

Reverse
TAGCGTTTCCGCAACTCTCG

NM_001432.2
EREG
Forward
CTGCAGGTGTGAAGTGGGTT

Reverse
GTGGAACCGACGACTGTGAT

NM_015713.4
RRM2B
Forward
AGAGTTCTCGCCGGTTTGTC

Reverse
GTCGACCTCTTCTGCTGTCC

NM_016848.5
SHC3
Forward
GCTTTTGCTGTGAGCAGCC

Reverse
CCACCGTTAAAAGCCAGCAC

NM_183001.4
SHC1
Forward
CTTGGGAGCTACATTGCCTGT

Reverse
TCAAAAAGCTCTCTGCCTGGAC

NM_014454.2
SESN1
Forward
TTGACAGCTCCACAACGTGA

Reverse
TGTACACGAAAGGGCAGTCT

NM_005259.2
MSTN
Forward
TTGACATGAACCCAGGCACT

Reverse
GTCCTGGGAAGGTTACAGCA

NM_002478.4
MYOD1
Forward
CGCCAGGATATGGAGCTACT

Reverse
GAGTGCTCTTCGGGTTTCAG

NM_005902.3
SMAD3
Forward
CATGTCGTCCATCCTGCCTT

Reverse
TTGGTGTTGACGTTCTGCGT

(b)

Cycling step
Temperature
Time
Number of cycles

Enzyme activation/initial DNA denaturation
95°C
30 seconds
1

Denaturation
95°C
5 seconds
40

Annealing/extension
60°C
30 seconds

Melt curve
65°C to 95°C (in 0.5°C increments)
5 seconds
1

By referring to each REV value of the targeted gene, the fold change (FC) can be calculated by using the following equation:

2.7. Statistical Analysis

Microarray data was analysed by using Partek Genomic Suite (v. 6.6; Partek, St. Louis, MO), and the differentially expressed gene lists were filtered based on a fold change of 1.5 and a significance level of by using two-way analysis of variance (2-way ANOVA). The relevant biological function and reaction pathway was identified based on GSEA analysis at a significance level of and KEGG analysis at an enrichment score by using the Partek Genomic Suite.

The REV data in qPCR are presented as error of the mean (SEM). Statistical analysis was performed with the software IBM SPSS Statistics (version 20). Independent sample test was used to determine the significant differences in between the SIPS control and TRF-treated groups. For all of the tests, was considered statistically significant.

3. Results

3.1. Quality Control Assessment of the Samples and the Hierarchical Clustering of Significantly Expressed Genes

Principal component analysis (PCA) is a multivariate statistic which allows viewing of separation between groups of replicates. The untreated young control, SIPS, and TRF-posttreated groups were well separated (Figure 1(a)). Hierarchical cluster analysis was performed to organize genes into cluster based on their similarities of expression. The upregulation of gene expression was indicated in red, whereas the downregulation of gene expression was indicated in blue. Clustering analysis was able to distinguish gene expressions between untreated young control and SIPS groups as well as between TRF-posttreated and SIPS groups (Figure 1(b)).

(a)

(b)

(c)

Figure 1: (a) PCA and (b) hierarchical clustering of the data. Clustering analysis was able to distinguish gene expression between untreated young control and SIPS control as well as between the TRF-treated group and the SIPS control group. (c) There were a total of 41 genes and 905 genes significantly expressed in between SIPS control and untreated young control and in between TRF-posttreated SIPS cells and SIPS control, respectively.

3.2. Identification of Gene Expression Changes Associated with SIPS Myoblasts

The gene expression analysis using Partek Genomic Suite was performed to identify changes in the SIPS myoblasts. Statistical analysis of two-way analysis of variance (2-way ANOVA) revealed that a total of 41 genes were significantly regulated in SIPS myoblasts as compared to untreated young control cells (fold or fold ; ); i.e., 11 genes were upregulated and 30 genes were downregulated (Figure 1(c)). The complete list of 41 differentially expressed genes is available in Table S01, Supplementary Materials.

3.3. Identification of Gene Expression Changes Associated with TRF-Post-treatment on SIPS Myoblasts

The gene expression analysis using Partek Genomic Suite was performed to identify changes in TRF-posttreated SIPS myoblasts. Statistical analysis of two-way analysis of variance (2-way ANOVA) revealed that a total of 905 genes were significantly regulated in TRF-posttreated SIPS myoblasts as compared to the SIPS group (fold or fold ; ); i.e., 378 genes were upregulated and 527 genes were downregulated (Figure 1(c)). The complete list of 905 differentially expressed genes is available in Table S02, Supporting Materials. At present, only selected differentially expressed genes including growth differentiation factor 15 (GDF15), epiregulin (EREG), ribonucleotide reductase M2B (RRM2B), SHC (Src homology 2 domain containing) transforming protein 3 (SHC3), SHC transforming protein 1 (SHC1), sestrin 1 (SESN1), myostatin (MSTN), myogenic differentiation 1 (MYOD1), and SMAD family member 3 (SMAD3) that have attracted our interest will be discussed. The chosen genes regulated by TRF treatment were selected based on the biological processes and KEGG pathway analysis.

3.4. Biological Processes and Pathways Affected by SIPS

GSEA analysis was carried out by using the Partek Genomic Suite. GSEA analysis revealed the selected significant biological processes involved in SIPS myoblasts compared to the untreated young control group () (Table 2). The positive value of the normalized enrichment score (NES) indicated an increment in the regulation of the biological process, whereas the negative value of NES indicated a reduction in the regulation of the stated biological process. SIPS myoblasts showed a significant increase in cellular biogenic amine metabolic process and apoptosis but decreased in activities of lipoprotein and regulation of skeletal muscle cell differentiation.

Table 2: GSEA analysis on the biological processes regulated by the stress-induced premature senescence as compared to the untreated young control ().

GO accession
Biological process
NES
value

GO:0006576
Cellular biogenic amine metabolic process
1.33
2.63E − 02

GO:0044106
Cellular amine metabolic process
1.33
2.63E − 02

GO:0046885
Regulation of hormone biosynthetic process
−1.40
3.17E − 02

GO:0051004
Regulation of lipoprotein lipase activity
−1.32
3.28E − 02

GO:0070874
Negative regulation of glycogen metabolic process
−1.44
3.39E − 02

GO:0032106
Positive regulation of response to extracellular stimulus
−1.48
3.45E − 02

GO:0032109
Positive regulation of response to nutrient levels
−1.48
3.45E − 02

GO:0031442
Positive regulation of mRNA 3′-end processing
−1.24
3.57E − 02

GO:0043001
Golgi to plasma membrane protein transport
−1.41
3.64E − 02

GO:2000973
Regulation of pro-B cell differentiation
−1.69
3.77E − 02

GO:0032494
Response to peptidoglycan
1.40
3.85E − 02

GO:0006400
tRNA modification
1.50
3.92E − 02

GO:0045807
Positive regulation of endocytosis
−1.34
4.11E − 02

GO:0006970
Response to osmotic stress
−1.15
4.17E − 02

GO:0090199
Regulation of release of cytochrome c from mitochondria
1.29
4.35E − 02

GO:0042953
Lipoprotein transport
−1.18
4.35E − 02

GO:0044872
Lipoprotein localization
−1.18
4.35E − 02

GO:0061418
Regulation of transcription from RNA polymerase II promoter in response to hypoxia
−1.52
4.35E − 02

GO:0048644
Muscle organ morphogenesis
−1.70
4.35E − 02

GO:0022615
Protein to membrane docking
−1.49
4.41E − 02

GO:0035563
Positive regulation of chromatin binding
1.55
4.44E − 02

GO:0048259
Regulation of receptor-mediated endocytosis
−1.25
4.48E − 02

GO:0032922
Circadian regulation of gene expression
−1.25
4.55E − 02

GO:0006694
Steroid biosynthetic process
−1.37
4.55E − 02

GO:2001014
Regulation of skeletal muscle cell differentiation
−1.57
4.55E − 02

GO:2000641
Regulation of early endosome to late endosome transport
−1.31
4.62E − 02

GO:0043112
Receptor metabolic process
−1.25
4.69E − 02

GO:0006891
Intra-Golgi vesicle-mediated transport
−1.38
4.69E − 02

GO:0035330
Regulation of hippo signalling
−1.44
4.69E − 02

GO:0035640
Exploration behavior
−1.47
4.69E − 02

GO:0006270
DNA replication initiation
1.46
4.76E − 02

GO:0031536
Positive regulation of exit from mitosis
1.29
4.76E − 02

GO:0048020
CCR chemokine receptor binding
−1.41
4.76E − 02

GO:0017144
Drug metabolic process
−1.42
4.76E − 02

GO:2000095
Regulation of Wnt signalling pathway, planar cell polarity pathway
−1.69
4.76E − 02

GO:0042347
Negative regulation of NF-kappaB import into nucleus
−1.37
4.84E − 02

GO:0046854
Phosphatidylinositol phosphorylation
−1.38
4.84E − 02

GO:0006901
Vesicle coating
−1.42
4.84E − 02

GO:0051045
Negative regulation of membrane protein ectodomain proteolysis
1.62
4.88E − 02

GO:0006335
DNA replication-dependent nucleosome assembly
1.51
4.88E − 02

GO:0034723
DNA replication-dependent nucleosome organization
1.51
4.88E − 02

GO:2000649
Regulation of sodium ion transmembrane transporter activity
−1.33
4.92E − 02

GO:0048260
Positive regulation of receptor-mediated endocytosis
−1.35
4.92E − 02

GO:0002381
Immunoglobulin production involved in immunoglobulin-mediated immune response
−1.36
4.92E − 02

GO:0018879
Biphenyl metabolic process
−1.45
4.92E − 02

3.5. Biological Processes and Pathways Affected by the TRF-Post-treatment on SIPS Myoblasts

GSEA analysis revealed the selected significant biological processes involved in response to TRF-posttreatment SIPS myoblasts compared to SIPS control myoblasts () (Table 3). TRF treatment has significantly increased the regulation of JNK cascade, cell growth, and adult walking behavior, but decreased the cell cycle activity. KEGG pathway analysis was carried out by using Partek Genomic Suite, and the data can be categorised according to the cluster of differentially expressed genes (fold or fold ; ) and the pathway ANOVA statistical method ().

Table 3: GSEA analysis on the biological processes regulated by the TRF-posttreated SIPS cells as compared to the SIPS control ().

GO accession
Biological process
NES
value

GO:0009165
Nucleotide biosynthetic process
−1.36
1.85E − 02

GO:0006338
Chromatin remodeling
−1.76
1.85E − 02

GO:0046328
Regulation of JNK cascade
1.21
1.96E − 02

GO:0030968
Endoplasmic reticulum unfolded protein response
1.71
2.04E − 02

GO:0032069
Regulation of nuclease activity
1.65
2.04E − 02

GO:0016558
Protein import into peroxisome matrix
1.41
2.13E − 02

GO:0030259
Lipid glycosylation
1.56
2.22E − 02

GO:0090501
RNA phosphodiester bond hydrolysis
−1.64
2.22E − 02

GO:0071695
Anatomical structure maturation
1.39
2.27E − 02

GO:0032869
Cellular response to insulin stimulus
1.35
2.27E − 02

GO:0016049
Cell growth
1.55
2.38E − 02

GO:0019321
Pentose metabolic process
1.44
2.44E − 02

GO:2001241
Positive regulation of the extrinsic apoptotic signalling pathway in absence of ligand
1.29
2.44E − 02

GO:2001239
Regulation of the extrinsic apoptotic signalling pathway in the absence of ligand
1.24
2.44E − 02

GO:0032092
Positive regulation of protein binding
1.64
2.50E − 02

GO:0045599
Negative regulation of fat cell differentiation
1.29
2.56E − 02

GO:0071479
Cellular response to ionizing radiation
−1.37
3.17E − 02

GO:0006308
DNA catabolic process
−1.56
3.28E − 02

GO:0000082
G1/S transition of mitotic cell cycle
−1.77
3.28E − 02

GO:0044843
Cell cycle G1/S phase transition
−1.77
3.28E − 02

GO:0090025
Regulation of monocyte chemotaxis
1.52
3.57E − 02

GO:0046325
Negative regulation of glucose import
1.34
3.57E − 02

GO:0010800
Positive regulation of peptidyl-threonine phosphorylation
−1.28
3.57E − 02

GO:0007127
Meiosis I
−1.66
3.64E − 02

GO:0002689
Negative regulation of leukocyte chemotaxis
1.81
3.70E − 02

GO:0006534
Cysteine metabolic process
1.32
3.70E − 02

GO:0090231
Regulation of spindle checkpoint
−1.61
3.70E − 02

GO:1902850
Microtubule cytoskeleton organization involved in mitosis
−1.73
3.70E − 02

GO:0032200
Telomere organization
−1.88
3.70E − 02

GO:0071300
Cellular response to retinoic acid
1.26
3.77E − 02

GO:0006302
Double-strand break repair
−1.88
3.77E − 02

GO:0031064
Negative regulation of histone deacetylation
1.47
3.85E − 02

GO:0010155
Regulation of proton transport
1.37
3.85E − 02

GO:0032924
Activin receptor signalling pathway
−1.35
3.85E − 02

GO:0051181
Cofactor transport
1.62
3.92E − 02

GO:0000060
Protein import into nucleus, translocation
−1.71
3.92E − 02

GO:1902668
Negative regulation of axon guidance
1.67
4.00E − 02

GO:0043388
Positive regulation of DNA binding
1.39
4.00E − 02

GO:0043320
Natural killer cell degranulation
−1.34
4.00E − 02

GO:0010887
Negative regulation of cholesterol storage
1.62
4.08E − 02

GO:0032845
Negative regulation of homeostatic process
1.47
4.08E − 02

GO:0051896
Regulation of protein kinase B signalling
1.33
4.08E − 02

GO:0008334
Histone mRNA metabolic process
−1.69
4.08E − 02

GO:0097191
Extrinsic apoptotic signalling pathway
1.22
4.17E − 02

GO:0002686
Negative regulation of leukocyte migration
1.53
4.26E − 02

GO:0048706
Embryonic skeletal system development
1.36
4.26E − 02

GO:0097035
Regulation of membrane lipid distribution
1.35
4.26E − 02

GO:0061157
mRNA destabilization
−1.72
4.26E − 02

GO:2000615
Regulation of histone H3-K9 acetylation
−1.73
4.26E − 02

GO:0072528
Pyrimidine-containing compound biosynthetic process
−1.88
4.26E − 02

GO:1903036
Positive regulation of response to wounding
1.35
4.35E − 02

GO:1900746
Regulation of vascular endothelial growth factor signalling pathway
−1.53
4.35E − 02

GO:0009303
rRNA transcription
−1.45
4.41E − 02

GO:0045080
Positive regulation of chemokine biosynthetic process
1.88
4.44E − 02

GO:0008207
C21-steroid hormone metabolic process
1.69
4.44E − 02

GO:0050795
Regulation of behavior
1.51
4.44E − 02

GO:1902107
Positive regulation of leukocyte differentiation
1.28
4.44E − 02

GO:0017157
Regulation of exocytosis
1.16
4.44E − 02

GO:0007098
Centrosome cycle
−1.42
4.44E − 02

GO:0001946
Lymphangiogenesis
−1.43
4.48E − 02

GO:0050919
Negative chemotaxis
1.68
4.55E − 02

GO:0060338
Regulation of the type I interferon-mediated signalling pathway
1.65
4.55E − 02

GO:0050748
Negative regulation of the lipoprotein metabolic process
1.56
4.55E − 02

GO:0038031
Noncanonical Wnt signalling pathway via JNK cascade
1.53
4.55E − 02

GO:0010935
Regulation of macrophage cytokine production
1.49
4.55E − 02

GO:0060907
Positive regulation of macrophage cytokine production
1.40
4.55E − 02

GO:0034661
ncRNA catabolic process
−1.71
4.55E − 02

GO:0090503
RNA phosphodiester bond hydrolysis, exonucleolytic
−1.59
4.62E − 02

GO:1902624
Positive regulation of neutrophil migration
1.69
4.65E − 02

GO:2000406
Positive regulation of T cell migration
1.63
4.65E − 02

GO:2000403
Positive regulation of lymphocyte migration
1.56
4.65E − 02

GO:1901725
Regulation of histone deacetylase activity
2.14
4.76E − 02

GO:1902667
Regulation of axon guidance
1.81
4.76E − 02

GO:0048841
Regulation of axon extension involved in axon guidance
1.73
4.76E − 02

GO:0050882
Voluntary musculoskeletal movement
1.51
4.76E − 02

GO:0042113
B cell activation
−1.19
4.76E − 02

GO:0072522
Purine-containing compound biosynthetic process
−1.29
4.76E − 02

GO:1901991
Negative regulation of mitotic cell cycle phase transition
−1.47
4.76E − 02

GO:0006919
Activation of cysteine-type endopeptidase activity involved in apoptotic process
−1.23
4.84E − 02

GO:2000757
Negative regulation of peptidyl-lysine acetylation
−1.80
4.84E − 02

GO:0035067
Negative regulation of histone acetylation
−1.83
4.84E − 02

GO:0007628
Adult walking behavior
1.94
4.88E − 02

GO:0021756
Striatum development
−1.31
4.92E − 02

GO:1901988
Negative regulation of cell cycle phase transition
−1.46
4.92E − 02

GO:0045185
Maintenance of protein location
−1.48
4.92E − 02

GO:0051053
Negative regulation of DNA metabolic process
−1.52
4.92E − 02

GO:0051258
Protein polymerization
−1.53
4.92E − 02

GO:0044774
Mitotic DNA integrity checkpoint
−1.68
4.92E − 02

GO:0009124
Nucleoside monophosphate biosynthetic process
−1.71
4.92E − 02

GO:0043487
Regulation of RNA stability
−1.75
4.92E − 02

GO:0034501
Protein localization to kinetochore
−1.82
4.92E − 02

GO:0000077
DNA damage checkpoint
−1.91
4.92E − 02

GO:0000079
Regulation of cyclin-dependent protein serine/threonine kinase activity
−2.01
4.92E − 02

Our KEGG pathway analysis showed that TRF treatment significantly modulated the p53 signalling pathway, FoxO signalling pathway, Wnt signalling pathway, cell cycle, and ErbB signalling pathway (Table 4). The regulation of gene expression involved in the stated pathway is presented in Figure 2.

Table 4: KEGG pathway analysis regulated by the TRF-posttreated SIPS cells as compared to the SIPS control () according to the (a) differential expression of gene and (b) pathway ANOVA analysis.

(a)

KEGG entry
Pathway
NES
value

hsa04110
Cell cycle
25.93
5.50E − 12

hsa03030
DNA replication
20.99
7.64E − 10

hsa04115
p53 signalling pathway
16.76
5.25E − 08

hsa05206
MicroRNAs in cancer
16.08
1.03E − 07

hsa03460
Fanconi anemia pathway
14.93
3.29E − 07

hsa05203
Viral carcinogenesis
14.45
5.30E − 07

hsa05200
Pathways in cancer
12.88
2.54E − 06

hsa03430
Mismatch repair
10.17
3.81E − 05

hsa05322
Systemic lupus erythematosus
10.00
4.53E − 05

hsa04114
Oocyte meiosis
9.11
1.11E − 04

hsa05034
Alcoholism
8.64
1.76E − 04

hsa03420
Nucleotide excision repair
7.96
3.50E − 04

hsa03440
Homologous recombination
6.78
1.13E − 03

hsa00900
Terpenoid backbone biosynthesis
6.72
1.21E − 03

hsa05219
Bladder cancer
6.38
1.70E − 03

hsa05166
HTLV-I infection
6.16
2.11E − 03

hsa00310
Lysine degradation
6.02
2.43E − 03

hsa05210
Colorectal cancer
5.56
3.86E − 03

hsa04914
Progesterone-mediated oocyte maturation
5.20
5.52E − 03

hsa04068
FoxO signalling pathway
5.10
6.10E − 03

hsa05205
Proteoglycans in cancer
4.75
8.61E − 03

hsa04978
Mineral absorption
4.50
1.11E − 02

hsa04390
Hippo signalling pathway
4.49
1.12E − 02

hsa05222
Small cell lung cancer
4.23
1.46E − 02

hsa05217
Basal cell carcinoma
4.06
1.72E − 02

hsa05212
Pancreatic cancer
4.04
1.76E − 02

hsa00480
Glutathione metabolism
3.40
3.34E − 02

hsa05214
Glioma
3.17
4.22E − 02

hsa04310
Wnt signalling pathway
3.16
4.25E − 02

(b)

KEGG entry
Pathway
value
Fold change

hsa05323
Rheumatoid arthritis
8.98E − 03
1.13

hsa04630
Jak-STAT signalling pathway
1.12E − 02
1.07

hsa04978
Mineral absorption
1.56E − 02
1.13

hsa00860
Porphyrin and chlorophyll metabolism
1.89E − 02
1.14

hsa04340
Hedgehog signalling pathway
1.93E − 02
1.10

hsa00520
Amino sugar and nucleotide sugar metabolism
2.06E − 02
1.11

hsa05217
Basal cell carcinoma
2.12E − 02
1.10

hsa00561
Glycerolipid metabolism
2.18E − 02
1.09

hsa00630
Glyoxylate and dicarboxylate metabolism
2.20E − 02
−1.16

hsa04330
Notch signalling pathway
2.22E − 02
1.08

hsa00564
Glycerophospholipid metabolism
2.33E − 02
1.07

hsa00100
Steroid biosynthesis
2.46E − 02
−1.20

hsa00040
Pentose and glucuronate interconversions
2.66E − 02
1.16

hsa00051
Fructose and mannose metabolism
2.76E − 02
1.10

hsa03050
Proteasome
2.79E − 01
1.11

hsa00980
Metabolism of xenobiotics by cytochrome P450
3.08E − 02
1.08

hsa00650
Butanoate metabolism
3.11E − 02
−1.13

hsa00052
Galactose metabolism
3.13E − 02
1.12

hsa04640
Hematopoeitic cell lineage
3.22E − 02
1.08

hsa03060
Protein export
3.34E − 02
1.13

hsa04130
SNARE interactions in vesicular transport
3.35E − 02
1.08

hsa04110
Cell cycle
3.39E − 02
−1.31

hsa04966
Collecting duct acid secretion
3.48E − 02
1.23

hsa03430
Mismatch repair
3.68E − 02
−1.38

hsa03030
DNA replication
3.70E − 02
−1.80

hsa03460
Fanconi anemia pathway
3.79E − 02
−1.29

hsa00533
Glycosaminoglycan biosynthesis-keratan sulfate
3.99E − 02
1.12

hsa04012
ErbB signalling pathway
4.04E − 02
1.05

hsa03450
Nonhomologous end-joining
4.25E − 02
−1.19

hsa04070
Phosphatidylinositol signalling system
4.28E − 02
1.06

hsa00190
Oxidative phosphorylation
4.33E − 02
1.08

hsa00730
Thiamine metabolism
4.41E − 02
1.17

hsa03440
Homologous recombination
4.43E − 02
−1.16

hsa00982
Drug metabolism - cytochrome P450
4.55E − 02
1.04

hsa00072
Synthesis and degradation of ketone bodies
4.65E − 02
−1.27

hsa00532
Glycosaminoglycan biosynthesis - chondroitin sulfate/dermatan sulfate
4.69E − 02
1.15

hsa04360
Axon guidance
4.74E − 02
1.05

hsa00280
Valine, leucine, and isoleucine degradation
4.93E − 02
−1.07

hsa04210
Apoptosis
4.96E − 02
1.06

hsa00300
Lysine biosynthesis
4.99E − 02
−1.47

(a)

(b)

(c)

(d)

(e)

Figure 2: Differential gene expression involved in the KEGG pathway regulated by TRF treatment, i.e., (a) cell cycle, (b) p53 signalling pathway, (c) FoxO signalling pathway, (d) Wnt signalling pathway, and (e) ErbB signalling pathway.

3.6. Microarray Result Validation

To confirm the microarray expression, we performed qPCR validation and found that all of the tested genes have consistent gene profiles. The REV value and fold change for all of the genes were consistent for both microarray analysis and qPCR analysis (Figure 3).

(a)

(b)

Figure 3: Microarray result validation. (a) The REV value and (b) the fold change were consistent between the microarray analysis and the qPCR analysis. The REV data are shown as . compared to SIPS control.

4. Discussion

Vitamin E, especially tocopherol, with a combination of other approaches, such as exercise, vitamin C, or selenium, has been reported to improve the condition of aged skeletal muscles by reducing oxidative stress and increasing the activities of antioxidant enzymes in the muscles of aged rats [20, 24]. Recently, one of the isomers of vitamin E, i.e., tocotrienol, has been proven for its effects in antioxidant defence enhancement and for improving the proliferation and differentiation in both replicative senescence and oxidative stress-induced premature myoblasts [22, 25, 26]. Khor et al. suggested that TRF reduced the senescence phenotypes in the skeletal muscle which may not only be limited to the encounter of oxidative stress but also instead be possibly associated with its regenerative capacity [23]. Little is known on the mechanism of tocotrienol towards the oxidative stress-associated senescence in myoblasts, especially human myoblasts. Thus, in this study, we revealed the novel insight into the differential gene expression by stress-induced human myoblasts with the treatment of TRF.

4.1. Alteration in Gene Expression and Biological Process in SIPS Cells

Hydrogen peroxide (H₂O₂) is a common inducer in the SIPS model in various cells [27, 28]. Research has shown that H₂O₂ downregulated the expression of miRNAs such as miR-15 and miR-106b families which contributes to some of the features of senescence cells. These features include the increased resistance to apoptosis and activation of p21CDKN1A. At the same time, it upregulates miR-182 which causes specific changes in senescence-associated gene expression [29]. Our GSEA analysis showed that SIPS has upregulated the cellular biogenic amine metabolic process in the cells while differential gene expression analysis showed that spermine oxidase (SMOX) was upregulated. Biogenic amine, such as polyamine, monoamine, and histamine, is involved in the mechanism of apoptosis progression [30]. The increasing expression of SMOX would increase the oxidation of spermine in the nucleus to spermidine, H₂O₂, and 3-aminopropanal and reduce the concentration of nuclear spermine, thus dysregulating the protective roles of spermine in free radical scavenging and DNA shielding and resulting in an overall increased potential for oxidative DNA damage in these cells [31]. Apoptosis has always been one of the suggested factors in the mass loss of skeletal muscle and muscle atrophy [32, 33], and our GSEA analysis was in line with this factor. The GSEA analysis showed the upregulation of cytochrome c released from mitochondria which is an indicator of early-stage apoptosis in SIPS myoblasts.

4.2. Alteration in Gene Expression, Biological Process, and Signalling Pathway in TRF-Post-treated SIPS Cells

4.2.1. ErbB Signalling Pathway

KEGG pathway analysis showed that TRF treatment on SIPS myoblasts significantly regulated a few biological processes and pathways related to cell proliferation, including the ErbB signalling pathway and FoxO signalling pathway. Several ErbB signalling-related genes, such as EGF, EGFR, EREG, SHC1, and SHC3, were significantly regulated by the treatment of TRF. The upregulation of SHC1 and SHC3 expression by 2.70-fold and 2.36-fold, respectively, by TRF treatment on SIPS myoblasts suggested the involvement of TRF in modulating the ErbB pathway, hence improving the regenerative capacity of skeletal muscle via cell proliferation. A similar effect was observed in C. elegans, in which SHC1 activated JNK signalling by binding to the MEK-1 kinase and hence regulating stress response and aging [34]. Epiregulin (EREG), an ErbB-signalling related gene, was upregulated with a 5.68-fold in TRF-posttreatment SIPS myoblasts compared to the SIPS group. Upregulation of EREG expression was reported before in C2C12 mouse myoblast cells after 4 hours from differentiation of myoblast cells. However, downregulation of the MRF gene and regulation of canonical Wnt signalling by the TRF on SIPS myoblasts minimised the possibilities of differentiation of human myoblasts (CHQ5B) in this study. Other studies with human cells showed that upregulation of EREG expression improved the proliferation ability of various human cells, i.e., mesenchymal stem cells, keratinocytes, and fibroblasts [35–37]. Hence, upregulation of EREG expression by TRF-post-treatment in SIPS myoblasts suggested a similar mechanism, i.e., modulation of the ErbB pathway which leads to increased proliferation capacity of myoblasts.

4.2.2. Myostatin (MSTN)

Unpredictably, our findings showed that myostatin (MSTN), a negative regulator in the muscle growth and regenerative potential of skeletal muscle, was downregulated significantly by 5.46-fold. This would be a novel finding in the modulation of muscle regeneration by TRF. Exposure of myostatin to mouse C2C12 myoblast cells reduced the proliferation and protein synthesis and thus prevented the progression of cells from the G1 to S phase in the cell cycle [38, 39]. On the other hand, aside from an increment in total RNA and protein synthesis rate, mice with myostatin knockout had a larger size of myotube [40]. A study showed that muscle-associated senescence upregulated the expression of myostatin, but antagonists of myostatin activated the satellite cells and increased the protein level of Pax7 and MyoD which in turn improved the regenerative capacity of muscle cells [41, 42].

The signalling pathways for myostatin can be divided into SMAD-mediated and non-SMAD pathways. The present microarray analysis showed that the treatment of TRF on SIPS myoblasts modulated the FoxO signalling pathway through downregulation of MSTN and SMAD3. FoxO and SMAD are involved in the regulation of muscle growth through amplification of atrophy response and activation of MSTN expression [43]. SMAD3-mediated myostatin signalling increased the sarcomeric protein degradation via the ubiquitin-proteasome pathway by stimulating FoxO1 and atrogin-1 expression [44]. In this study, the downregulation of MSTN and SMAD3 by TRF treatment suggested that the reduction in the SMAD-mediated myostatin signalling pathway and TRF treatment would reduce the protein degradation in the SIPS myoblasts.

4.2.3. Ribonucleotide Reductase M2B (RRM2B)

Modulation of the ErbB signalling pathway and the FoxO signalling pathway by TRF treatment suggested that the mechanism involved might be related to cell proliferation. However, at the same time KEGG analysis demonstrated that TRF regulated the satellite cells to remain in the quiescent state through the p53 signalling, cell cycle, and Wnt signalling pathways. Interestingly, these findings showed a contradiction. Nevertheless, recent studies showed that the satellite cells are a heterogeneous population as they consist of satellite stem cells and committed progenitors [45]. Symmetric division of satellite cells allowed the cells to divide and expand the satellite stem cell subpopulation, whereas asymmetric division of satellite cells would maintain the stem cell population which is involved in the self-renewal and generation of myogenic progenitors [46, 47]. Dumont et al. suggested that a dynamic balance must exist in between the symmetric and asymmetric division even though the satellite cells are able to choose whether to perform symmetric or asymmetric division, and it allows them to coordinate their activity with the needs of the regenerating muscle [46]. An imbalance in the ratio of symmetric and asymmetric division would deteriorate the regenerative capacity of muscles. These were observed in the aging cells with a disruption in the satellite cells’ ability to self-renew or return to the quiescent state [48, 49].

The TRF-post-treatment on SIPS myoblasts has targeted p53 signalling by upregulating the expression of the p53 target gene, i.e., RRM2B and SESN1. RRM2B activation is initiated by DNA damage and further involved in DNA repair regulated by p53 [50, 51]. Dysfunction of RRM2B was first reported in mitochondrial DNA depletion syndrome which caused early fatality in children [52, 53]. Kuo et al. reported that the expression of RRM2B was highly induced during oxidative stress in the human primer fibroblast (IMR90 cell) to stimulate antioxidant reaction [50]. Silencing of RRM2B expression leads to an increase in reactive oxygen species level, mitochondrial membrane depolarisation, and premature senescence in young fibroblasts. Thus, upregulation of RRM2B expression by TRF was suggested to stimulate the antioxidant defence in order to counteract with the increasing stress level in SIPS myoblasts.

4.2.4. Sestrins

Aside from RRM2B, SESN1 was also upregulated by the TRF. Sestrins were the third recently identified hallmark of sarcopenia [54]. Sestrin expression was upregulated in DNA damaged cells, oxidative stress condition, and hypoxia [55]. SESN1 and SESN2 are p53-regulated genes which are involved in the regulation of autophagy and cell viability, whereas SESN3 is a FoxO-regulated gene which in turn activated SESN1 [56–58]. Inhibition of mTORC1 activation via the sestrin-AMPK pathway was reported to extend the lifespan of mammalia [59–61]. A more specific study was carried out to investigate the expression of sestrins towards the skeletal muscle [62]. The thorax of adult Drosophila mainly consists of skeletal muscle enriched with Drosophila sestrins (dSesn). dSesn-null flies experienced acceleration in aging-associated degeneration, such as loss of sarcomeric structure and abnormality in mitochondria. However, treatment with vitamin E effectively prevented the deterioration in skeletal muscle and cardiac muscle by reducing the involvement of ROS [62].

GSEA and KEGG pathway analysis showed that the cell cycle was downregulated by TRF treatment in SIPS myoblasts. This finding was in contrast with the findings which reported that TRF reduced the cell cycle arrest in senescence human fibroblast cells [63]. However, according to Blagosklonny, cell cycle arrest does not absolutely refer to senescence and vice versa [64]. Cell cycle arrest actually induced the cells to proceed to another stage of the cell cycle, such as quiescence, senescence, apoptosis, motility, and differentiation [65]. Skeletal muscle satellite cells withdraw from the cell cycle for two purposes, i.e., to return to the quiescence state and carry out self-renewal or to differentiate and generate new muscle fibres. These withdrawals can be differentiated by the differential expression of genes or pathway activation. Notch signalling was activated, and Spry1 expressions were upregulated when the cells return to the quiescence state, whereas Delta1 expression was upregulated for the cells to differentiate after withdrawing from the cell cycle [45, 46]. However, in our study, neither Spry1 nor Delta1 expression was regulated by TRF treatment. Instead, the expression of Spry4 was upregulated and the expression of Fgf1 was downregulated by the TRF. Downregulation of Fgf1 was once reported in the inhibition of mouse myoblast differentiation [66, 67]. Furthermore, upregulation of Fgf2 was reported in the activation of satellite cells and in turn increased the expression of Twist2 and Spry4, thus inhibiting the differentiation of mouse mesenchyme stem cells [68, 69]. Hence, we proposed that the withdrawal from the cell cycle of SIPS myoblasts posttreated with TRF was not due to differentiation, as differentiation was inhibited by downregulation of Fgf1 and upregulation of Spry4. Instead, the TRF promoted the myoblast cells to exit the cell cycle and return to their quiescence state.

4.2.5. Myogenic Regulatory Factor (MRF) and Wnt Signalling Pathway

The effect of TRF towards expression of the myogenic regulatory factor (MRF) was in line with the suggestion that the myoblasts exit the cell cycle for the maintenance of the quiescence cell population. The myogenic potential of satellite cells will highly depend on the expression of Pax and MRF (MyoD, Myf5, myogenin, and MRF4) [70]. Expression of Myf5 and/or MyoD was upregulated during the activation of satellite cells to the myoblast and early myogenic differentiation [71–73], whereas differentiation of myoblasts would upregulate the expression of myogenin and MRF4 (also known as Myf6) [73]. TRF treatment has downregulated the expression of Myf5, MyoD1, and Myf6, which means that TRF treatment did not promote the myoblast cells to withdraw from the cell cycle for differentiation.

The expression of MRF was regulated by the Wnt signalling pathway during the development of the embryo. However, in the adult skeletal muscle, the canonical Wnt signalling pathway regulated the differentiation of muscle satellite cells, whereas the noncanonical Wnt signalling pathway mediated the self-renewal of satellite stem cells and the growth of muscle fibres [74]. Our GSEA analysis revealed that the noncanonical Wnt signalling pathway was significantly regulated by TRF treatment. Among the Wnt involved in the noncanonical Wnt signalling pathway (Wnt4, Wnt5a, Wnt5b, Wnt8a, Wnt8b, Wnt10a, and Wnt10b), TRF treatment has upregulated the expression of Wnt5a and Wnt7b. Studies reported that Wnt were expressed at different times of injury in order to promote regeneration [75, 76]. Wnt5a, Wnt5b, and Wnt7a were upregulated at the early stage of regeneration, and Wnt7b and Wnt3a were regulated at the final stage after injury. The regulation of the Wnt signalling pathway, cell cycle, and p53 signalling by TRF treatment suggested the promotion of satellite cells to return to the quiescence state and maintain the population of quiescence cells.

4.2.6. Growth Differentiation Factor 15 (GDF15)

Another critical finding of our microarray analysis was the expression of GDF15 which was highly upregulated by 14.9-fold. The expression of GDF15 and its mechanism involved in the CHQ5B cells were not well studied. Previously, GDF15 was reported as a negative regulator in skeletal muscle growth [77, 78]. Senescence, smoking, and environmental factors would increase the GDF15 level [79]. The levels of GDF15 increased in patients experiencing intensive care unit acquired muscle weakness (ICUAW) or muscle atrophy [80, 81]. However, aside from a high level of GDF15, SMAD2/3 was activated by GDF15 in the ICUAW patients and this was in contrast with our findings. Findings showed that SMAD3 expression was downregulated by TRF treatment. GDF15 prevents the ROS production and exhibits an antiapoptotic effect and cell proliferation regulation [78, 82, 83]. Hence, the conclusion on the activity of GDF15 towards CHQ5B cells remains unknown due to its lack of investigation. Development of therapeutic interventions with GDF15 or anti-GDF15 agents remains difficult until the mechanism that drives its activity is revealed with more evidences.

5. Conclusions

At present, most of the studies focused on the effect of tocopherol on the skeletal muscles, but less in vitro findings were reported on the effects of tocotrienol towards human skeletal muscle cells and the mechanism involved remains unclear. Recent studies showed that muscle regeneration does not solely depend on the myogenic proliferation of the satellite cell as prolonged imbalance between the expansion and maintenance of the satellite stem cell population leads to impaired muscle regeneration [46]. Our findings proposed that TRF treatment not only promotes the proliferation capacity of SIPS myoblasts through regulation of the ErbB signalling pathway (upregulation of expression of EREG, SHC1, and SHC3) and FoxO signalling pathway (downregulation of expression of MSTN and SMAD3). At the same time, TRF treatment is proposed to modulate the renewal of satellite cells through regulation of p53 signalling (upregulation of RRM2B and SESN1), cell cycle, Wnt signalling pathway, and expression of MRF. Even though these findings were exciting, more extensive studies such as proteomic analysis and various time points of TRF treatments in the SIPS myoblast model are suggested in order to give a more thorough idea on the involvement of TRF in the regenerative capacity and mechanism of skeletal muscles.

Abbreviations

AGCC: | Affymetrix GeneChip Command Console
aRNA: | Amplified RNA
CEL: | Cell intensity file
Ct: | Threshold cycle
DMEM: | Dulbecco’s modified Eagle medium
EGFR: | Epidermal growth factor receptor
EREG: | Epiregulin
GAPDH: | Glyceraldehyde 3-phosphate dehydrogenase
GDF15: | Growth differentiation factor 15
GSEA: | Gene set enrichment analysis
H₂O₂: | Hydrogen peroxide
KEGG: | Kyoto Encyclopedia of Genes and Genomes
MRF: | Myogenic regulatory factor
Myf5: | Myogenic factor 5
MyoD: | Myogenic differentiation 1
PCA: | Principal component analysis
qPCR: | Quantitative real-time polymerase chain reaction
REV: | Relative expression value
RIN: | RNA integrity number
SIPS: | Stress-induced premature senescence
SMOX: | Spermine oxidase
TRF: | Tocotrienol-rich fraction.

Data Availability

The data used to support the findings of this study are included within the article and supplementary information files.

Conflicts of Interest

The authors declare that there is no conflict of interest regarding the publication of this article.

Authors’ Contributions

JJL, NAK, and WZWN conceived and designed the experiments. VM provided the human satellite cells CHQ5B and technical guidance on CHQ5B cell culture. JJL performed the experiments and analysed the data. JJL and NAK drafted the manuscript. All authors read and approved the final manuscript.

Acknowledgments

This research was financially supported by the grant from Universiti Kebangsaan Malaysia (UKM FF-03-FRGS0034-2010). We would like to acknowledge Dr. Vincent Mouly from UMRS 787, Institut de Myologie, INSERM, Université Pierre et Marie Curie, Paris, France, for providing us the human satellite cells CHQ5B.

Supplementary Materials

Figure S01: RNA integrity number (RIN) assessed by the electropherogram bioanalyzer for the (a) untreated young control cells, (b) SIPS control, and (c) TRF-posttreated SIPS cells. Figure S02: the specificity of primers assessed by (a–j) standard curve and melt curve analysis of each pair of primers and (k) agarose gel electrophoresis that was performed on the PCR products. Table S01: the complete list of 41 differentially expressed genes associated with stress-induced premature senescent control cells as compared to untreated young control cells (fold change < −1.5 or fold change > 1.5; ). Table S02: the complete list of 905 differentially expressed genes associated with TRF-posttreated SIPS cells as compared to SIPS control cells (fold change < −1.5 or fold change > 1.5; ). (Supplementary Materials)

References

A. J. Cruz-Jentoft, F. Landi, E. Topinkova, and J.-P. Michel, “Understanding sarcopenia as a geriatric syndrome,” Current Opinion in Clinical Nutrition and Metabolic Care, vol. 13, no. 1, pp. 1–7, 2010.

N. H. Farina, M. Hausburg, N. D. Betta et al., “A role for RNA post-transcriptional regulation in satellite cell activation,” Skeletal Muscle, vol. 2, no. 1, p. 21, 2012.

P. Kwan, “Sarcopenia, a neurogenic syndrome?” Journal of Aging Research, vol. 2013, Article ID 791679, 10 pages, 2013.

K. S. Nair, “Aging muscle,” The American Journal of Clinical Nutrition, vol. 81, no. 5, pp. 953–963, 2005.

E. Barbieri and P. Sestili, “Reactive oxygen species in skeletal muscle signaling,” Journal of Signal Transduction, vol. 2012, Article ID 982794, 17 pages, 2012.

A. Fanzani, V. M. Conraads, F. Penna, and W. Martinet, “Molecular and cellular mechanisms of skeletal muscle atrophy: an update,” Journal of Cachexia, Sarcopenia and Muscle, vol. 3, no. 3, pp. 163–179, 2012.

T. Braun and M. Gautel, “Transcriptional mechanisms regulating skeletal muscle differentiation, growth and homeostasis,” Nature Reviews Molecular Cell Biology, vol. 12, no. 6, pp. 349–361, 2011.

M. Romanick, L. V. Thompson, and H. M. Brown-Borg, “Murine models of atrophy, cachexia, and sarcopenia in skeletal muscle,” Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease, vol. 1832, no. 9, pp. 1410–1420, 2013.

C. A. Goodman, R. M. McNally, F. M. Hoffmann, and T. A. Hornberger, “Smad3 induces atrogin-1, inhibits mTOR and protein synthesis, and promotes muscle atrophy in vivo,” Molecular Endocrinology, vol. 27, no. 11, pp. 1946–1957, 2013.

A. S. Brack, M. J. Conboy, S. Roy et al., “Increased Wnt signaling during aging alters muscle stem cell fate and increases fibrosis,” Science, vol. 317, no. 5839, pp. 807–810, 2007.

B. Gao, K. Li, Y. Y. Wei et al., “Zinc finger protein 637 protects cells against oxidative stress-induced premature senescence by mTERT-mediated telomerase activity and telomere maintenance,” Cell Death & Disease, vol. 5, no. 7, article e1334, 2014.

J. Jamal, M. R. Mustafa, and P.-F. Wong, “Paeonol protects against premature senescence in endothelial cells by modulating Sirtuin 1 pathway,” Journal of Ethnopharmacology, vol. 154, no. 2, pp. 428–436, 2014.

J.-S. Kim, E.-J. Kim, H.-J. Kim, J.-Y. Yang, G.-S. Hwang, and C.-W. Kim, “Proteomic and metabolomic analysis of H2O2-induced premature senescent human mesenchymal stem cells,” Experimental Gerontology, vol. 46, no. 6, pp. 500–510, 2011.

D. Volonte and F. Galbiati, “Polymerase I and transcript release factor (PTRF)/Cavin-1 is a novel regulator of stress-induced premature senescence,” Journal of Biological Chemistry, vol. 286, no. 33, pp. 28657–28661, 2011.

M. Giorgio, M. Trinei, E. Migliaccio, and P. G. Pelicci, “Hydrogen peroxide: a metabolic by-product or a common mediator of ageing signals?” Nature Reviews Molecular Cell Biology, vol. 8, no. 9, pp. 722–728, 2007.

S. C. Khor, N. Abdul Karim, W. Z. Wan Ngah, Y. A. Mohd Yusof, and S. Makpol, “Vitamin E in sarcopenia: current evidences on its role in prevention and treatment,” Oxidative Medicine and Cellular Longevity, vol. 2014, Article ID 914853, 16 pages, 2014.

S.-F. Chin, J. Ibahim, S. Makpol et al., “Tocotrienol rich fraction supplementation improved lipid profile and oxidative status in healthy older adults: a randomized controlled study,” Nutrition & Metabolism, vol. 8, no. 1, p. 42, 2011.

S. Makpol, A. Zainuddin, K. H. Chua, Y. A. Yusof, and W. Z. Ngah, “Gamma-tocotrienol modulation of senescence-associated gene expression prevents cellular aging in human diploid fibroblasts,” Clinics, vol. 67, no. 2, pp. 135–143, 2012.

A. A. Qureshi, X. Tan, J. C. Reis et al., “Inhibition of nitric oxide in LPS-stimulated macrophages of young and senescent mice by δ-tocotrienol and quercetin,” Lipids in Health and Disease, vol. 10, no. 1, p. 239, 2011.

M. J. Ryan, H. J. Dudash, M. Docherty et al., “Vitamin E and C supplementation reduces oxidative stress, improves antioxidant enzymes and positive muscle work in chronically loaded muscles of aged rats,” Experimental Gerontology, vol. 45, no. 11, pp. 882–895, 2010.

A. C. Howard, A. K. McNeil, and P. L. McNeil, “Promotion of plasma membrane repair by vitamin E,” Nature Communications, vol. 2, no. 1, p. 597, 2011.

J. Jye Lim, W. Zurinah Wan Ngah, V. Mouly, and N. A. Karim, “Reversal of myoblast aging by tocotrienol rich fraction posttreatment,” Oxidative Medicine and Cellular Longevity, vol. 2013, Article ID 978101, 11 pages, 2013.

V. Renault, L.-E. Thornell, G. Butler-Browne, and V. Mouly, “Human skeletal muscle satellite cells: aging, oxidative stress and the mitotic clock,” Experimental Gerontology, vol. 37, no. 10-11, pp. 1229–1236, 2002.

S. G. Harsini, M. Habibiyan, M. M. Moeini, and A. R. Abdolmohammadi, “Effects of dietary selenium, vitamin E, and their combination on growth, serum metabolites, and antioxidant defense system in skeletal muscle of broilers under heat stress,” Biological Trace Element Research, vol. 148, no. 3, pp. 322–330, 2012.

S. C. Khor, A. M. Razak, W. Z. Wan Ngah, Y. A. Mohd Yusof, N. Abdul Karim, and S. Makpol, “The tocotrienol-rich fraction is superior to tocopherol in promoting myogenic Differentiation in the Prevention of Replicative Senescence of Myoblasts,” PLoS One, vol. 11, no. 2, article e0149265, 2016.

S. C. Khor, W. Z. Wan Ngah, Y. A. Mohd Yusof, N. Abdul Karim, and S. Makpol, “Tocotrienol-rich fraction ameliorates antioxidant defense mechanisms and improves replicative senescence-associated oxidative stress in human myoblasts,” Oxidative Medicine and Cellular Longevity, vol. 2017, Article ID 3868305, 17 pages, 2017.

A. Mougeolle, S. Poussard, M. Decossas, C. Lamaze, O. Lambert, and E. Dargelos, “Oxidative stress induces caveolin 1 degradation and impairs caveolae functions in skeletal muscle cells,” PLoS One, vol. 10, no. 3, article e0122654, 2015.

Y. Wang, M. N. Scheiber, C. Neumann, G. A. Calin, and D. Zhou, “MicroRNA regulation of ionizing radiation-induced premature senescence,” International Journal of Radiation Oncology, Biology, Physics, vol. 81, no. 3, pp. 839–848, 2011.

G. Li, C. Luna, J. Qiu, D. L. Epstein, and P. Gonzalez, “Alterations in microRNA expression in stress-induced cellular senescence,” Mechanisms of Ageing and Development, vol. 130, no. 11-12, pp. 731–741, 2009.

A. Toninello, M. Salvi, P. Pietrangeli, and B. Mondovì, “Biogenic amines and apoptosis: minireview article,” Amino Acids, vol. 26, no. 4, pp. 339–343, 2004.

T. Murray-Stewart, Y. Wang, A. Goodwin, A. Hacker, A. Meeker, and R. A. Casero Jr, “Nuclear localization of human spermine oxidase isoforms – possible implications in drug response and disease etiology,” FEBS Journal, vol. 275, no. 11, pp. 2795–2806, 2008.

E. Marzetti, R. Calvani, R. Bernabei, and C. Leeuwenburgh, “Apoptosis in skeletal myocytes: a potential target for interventions against sarcopenia and physical frailty – a mini-review,” Gerontology, vol. 58, no. 2, pp. 99–106, 2012.

S. E. Wohlgemuth, A. Y. Seo, E. Marzetti, H. A. Lees, and C. Leeuwenburgh, “Skeletal muscle autophagy and apoptosis during aging: effects of calorie restriction and life-long exercise,” Experimental Gerontology, vol. 45, no. 2, pp. 138–148, 2010.

E. Neumann-Haefelin, W. Qi, E. Finkbeiner, G. Walz, R. Baumeister, and M. Hertweck, “SHC-1/p52Shc targets the insulin/IGF-1 and JNK signaling pathways to modulate life span and stress response in C. elegans,” Genes & Development, vol. 22, no. 19, pp. 2721–2735, 2008.

Y. Cao, D. S. Xia, S. R. Qi et al., “Epiregulin can promote proliferation of stem cells from the dental apical papilla via MEK/Erk and JNK signalling pathways,” Cell Proliferation, vol. 46, no. 4, pp. 447–456, 2013.

C. Lindvall, M. Hou, T. Komurasaki et al., “Molecular characterization of human telomerase reverse transcriptase-immortalized human fibroblasts by gene expression profiling: activation of the epiregulin gene,” Cancer Research, vol. 63, no. 8, pp. 1743–1747, 2003.

Y. Shirakata, T. Komurasaki, H. Toyoda et al., “Epiregulin, a novel member of the epidermal growth factor family, is an autocrine growth factor in normal human keratinocytes,” Journal of Biological Chemistry, vol. 275, no. 8, pp. 5748–5753, 2000.

W. E. Taylor, S. Bhasin, J. Artaza et al., “Myostatin inhibits cell proliferation and protein synthesis in C2C12 muscle cells,” American Journal of Physiology-Endocrinology and Metabolism, vol. 280, no. 2, pp. E221–E228, 2001.

M. Thomas, B. Langley, C. Berry et al., “Myostatin, a negative regulator of muscle growth, functions by inhibiting myoblast proliferation,” Journal of Biological Chemistry, vol. 275, no. 51, pp. 40235–40243, 2000.

J. Rodriguez, B. Vernus, M. Toubiana et al., “Myostatin inactivation increases myotube size through regulation of translational initiation machinery,” Journal of Cellular Biochemistry, vol. 112, no. 12, pp. 3531–3542, 2011.

A. Baumann, C. Ibebunjo, W. Grasser, and V. Paralkar, “Myostatin expression in age and denervation-induced skeletal muscle atrophy,” Journal of Musculoskeletal and Neuronal Interactions, vol. 3, no. 1, pp. 8–16, 2003.

V. Siriett, M. S. Salerno, C. Berry et al., “Antagonism of myostatin enhances muscle regeneration during sarcopenia,” Molecular Therapy, vol. 15, no. 8, pp. 1463–1470, 2007.

D. L. Allen and T. G. Unterman, “Regulation of myostatin expression and myoblast differentiation by FoxO and SMAD transcription factors,” American Journal of Physiology-Cell Physiology, vol. 292, no. 1, pp. C188–C199, 2007.

S. Lokireddy, V. Mouly, G. Butler-Browne et al., “Myostatin promotes the wasting of human myoblast cultures through promoting ubiquitin-proteasome pathway-mediated loss of sarcomeric proteins,” American Journal of Physiology-Cell Physiology, vol. 301, no. 6, pp. C1316–C1324, 2011.

S. Kuang, K. Kuroda, F. Le Grand, and M. A. Rudnicki, “Asymmetric self-renewal and commitment of satellite stem cells in muscle,” Cell, vol. 129, no. 5, pp. 999–1010, 2007.

N. A. Dumont, Y. X. Wang, and M. A. Rudnicki, “Intrinsic and extrinsic mechanisms regulating satellite cell function,” Development, vol. 142, no. 9, pp. 1572–1581, 2015.

Y. X. Wang, N. A. Dumont, and M. A. Rudnicki, “Muscle stem cells at a glance,” Journal of Cell Science, vol. 127, no. 21, pp. 4543–4548, 2014.

F. D. Price, J. von Maltzahn, C. F. Bentzinger et al., “Inhibition of JAK-STAT signaling stimulates adult satellite cell function,” Nature Medicine, vol. 20, no. 10, pp. 1174–1181, 2014.

M. T. Tierney, T. Aydogdu, D. Sala et al., “STAT3 signaling controls satellite cell expansion and skeletal muscle repair,” Nature Medicine, vol. 20, no. 10, pp. 1182–1186, 2014.

M.-L. Kuo, A. J. Sy, L. Xue et al., “RRM2B suppresses activation of the oxidative stress pathway and is up-regulated by P53 during senescence,” Scientific Reports, vol. 2, no. 1, p. 822, 2012.

R. D. S. Pitceathly, C. Smith, C. Fratter et al., “Adults with RRM2B-related mitochondrial disease have distinct clinical and molecular characteristics,” Brain, vol. 135, no. 11, pp. 3392–3403, 2012.

B. Bornstein, E. Area, K. M. Flanigan et al., “Mitochondrial DNA depletion syndrome due to mutations in the RRM2B gene,” Neuromuscular Disorders, vol. 18, no. 6, pp. 453–459, 2008.

A. Bourdon, L. Minai, V. Serre et al., “Mutation of RRM2B, encoding p53-controlled ribonucleotide reductase (p53R2), causes severe mitochondrial DNA depletion,” Nature Genetics, vol. 39, no. 6, pp. 776–780, 2007.

F. Sanchis-Gomar, H. Pareja-Galeano, S. Mayero, C. Perez-Quilis, and A. Lucia, “New molecular targets and lifestyle interventions to delay aging sarcopenia,” Frontiers in Aging Neuroscience, vol. 6, 2014.

J. H. Lee, A. V. Budanov, and M. Karin, “Sestrins orchestrate cellular metabolism to attenuate aging,” Cell Metabolism, vol. 18, no. 6, pp. 792–801, 2013.

A. V. Budanov, T. Shoshani, A. Faerman et al., “Identification of a novel stress-responsive gene Hi95 involved in regulation of cell viability,” Oncogene, vol. 21, no. 39, pp. 6017–6031, 2002.

V. Nogueira, Y. Park, C.-C. Chen et al., “Akt determines replicative senescence and oxidative or oncogenic premature senescence and sensitizes cells to oxidative apoptosis,” Cancer Cell, vol. 14, no. 6, pp. 458–470, 2008.

S. Velasco-Miguel, L. Buckbinder, P. Jean et al., “PA26, a novel target of the p53 tumor suppressor and member of the GADD family of DNA damage and growth arrest inducible genes,” Oncogene, vol. 18, no. 1, pp. 127–137, 1999.

A. V. Budanov and M. Karin, “p53 target genes Sestrin1 and Sestrin2 connect genotoxic stress and mTOR signaling,” Cell, vol. 134, no. 3, pp. 451–460, 2008.

W. Mair, I. Morantte, A. P. C. Rodrigues et al., “Lifespan extension induced by AMPK and calcineurin is mediated by CRTC-1 and CREB,” Nature, vol. 470, no. 7334, pp. 404–408, 2011.

R. A. Miller, D. E. Harrison, C. M. Astle et al., “Rapamycin, but not resveratrol or simvastatin, extends life span of genetically heterogeneous mice,” The Journals of Gerontology: Series A, vol. 66A, no. 2, pp. 191–201, 2011.

J. H. Lee, A. V. Budanov, E. J. Park et al., “Sestrin as a feedback inhibitor of TOR that prevents age-related pathologies,” Science, vol. 327, no. 5970, pp. 1223–1228, 2010.

S. Makpol, L. W. Durani, K. H. Chua, Y. A. Mohd Yusof, and W. Z. Wan Ngah, “Tocotrienol-rich fraction prevents cell cycle arrest and elongates telomere length in senescent human diploid fibroblasts,” Journal of Biomedicine and Biotechnology, vol. 2011, Article ID 506171, 11 pages, 2011.

M. V. Blagosklonny, “Cell cycle arrest is not yet senescence, which is not just cell cycle arrest: terminology for TOR-driven aging,” Aging, vol. 4, no. 3, pp. 159–165, 2012.

C. Gérard and A. Goldbeter, “The balance between cell cycle arrest and cell proliferation: control by the extracellular matrix and by contact inhibition,” Interface Focus, vol. 4, no. 3, article 20130075, 2014.

C. H. Clegg, T. A. Linkhart, B. B. Olwin, and S. D. Hauschka, “Growth factor control of skeletal muscle differentiation: commitment to terminal differentiation occurs in G1 phase and is repressed by fibroblast growth factor,” The Journal of Cell Biology, vol. 105, no. 2, pp. 949–956, 1987.

C. Conte, N. Ainaoui, A. Delluc-Clavières et al., “Fibroblast growth factor 1 induced during myogenesis by a transcription–translation coupling mechanism,” Nucleic Acids Research, vol. 37, no. 16, pp. 5267–5278, 2009.

J. V. Chakkalakal, K. M. Jones, M. A. Basson, and A. S. Brack, “The aged niche disrupts muscle stem cell quiescence,” Nature, vol. 490, no. 7420, pp. 355–360, 2012.

W.-T. Lai, V. Krishnappa, and D. G. Phinney, “Fibroblast growth factor 2 (Fgf2) inhibits differentiation of mesenchymal stem cells by inducing Twist2 and Spry4, blocking extracellular regulated kinase activation, and altering Fgf receptor expression levels,” Stem Cells, vol. 29, no. 7, pp. 1102–1111, 2011.

F. Le Grand and M. A. Rudnicki, “Skeletal muscle satellite cells and adult myogenesis,” Current Opinion in Cell Biology, vol. 19, no. 6, pp. 628–633, 2007.

D. D. W. Cornelison and B. J. Wold, “Single-cell analysis of regulatory gene expression in quiescent and activated mouse skeletal muscle satellite cells,” Developmental Biology, vol. 191, no. 2, pp. 270–283, 1997.

A. Montesano, P. Senesi, L. Luzi, S. Benedini, and I. Terruzzi, “Potential therapeutic role of L-carnitine in skeletal muscle oxidative stress and atrophy conditions,” Oxidative Medicine and Cellular Longevity, vol. 2015, Article ID 646171, 13 pages, 2015.

Y. X. Wang and M. A. Rudnicki, “Satellite cells, the engines of muscle repair,” Nature Reviews Molecular Cell Biology, vol. 13, no. 2, pp. 127–133, 2012.

J. von Maltzahn, N. C. Chang, C. F. Bentzinger, and M. A. Rudnicki, “Wnt signaling in myogenesis,” Trends in Cell Biology, vol. 22, no. 11, pp. 602–609, 2012.

A. S. Brack, I. M. Conboy, M. J. Conboy, J. Shen, and T. A. Rando, “A temporal switch from notch to Wnt signaling in muscle stem cells is necessary for normal adult myogenesis,” Cell Stem Cell, vol. 2, no. 1, pp. 50–59, 2008.

A. Polesskaya, P. Seale, and M. A. Rudnicki, “Wnt signaling induces the myogenic specification of resident CD45+ adult stem cells during muscle regeneration,” Cell, vol. 113, no. 7, pp. 841–852, 2003.

A. Kalinkovich and G. Livshits, “Sarcopenia – the search for emerging biomarkers,” Ageing Research Reviews, vol. 22, pp. 58–71, 2015.

S. Subramaniam, J. Strelau, and K. Unsicker, “Growth differentiation factor-15 prevents low potassium-induced cell death of cerebellar granule neurons by differential regulation of Akt and ERK pathways,” Journal of Biological Chemistry, vol. 278, no. 11, pp. 8904–8912, 2003.

R. Adela and S. K. Banerjee, “GDF-15 as a target and biomarker for diabetes and cardiovascular diseases: a translational prospective,” Journal of Diabetes Research, vol. 2015, Article ID 490842, 14 pages, 2015.

S. A. A. Bloch, J. Y. Lee, T. Syburra et al., “Increased expression of GDF-15 may mediate ICU-acquired weakness by down-regulating muscle microRNAs,” Thorax, vol. 70, no. 3, pp. 219–228, 2015.

S. A. A. Bloch, J. Y. Lee, S. J. Wort, M. I. Polkey, P. R. Kemp, and M. J. D. Griffiths, “Sustained elevation of circulating growth and differentiation factor-15 and a dynamic imbalance in mediators of muscle homeostasis are associated with the development of acute muscle wasting following cardiac surgery,” Critical Care Medicine, vol. 41, no. 4, pp. 982–989, 2013.

C. Carrillo-Garcia, S. Prochnow, I. K. Simeonova et al., “Growth/differentiation factor 15 promotes EGFR signalling, and regulates proliferation and migration in the hippocampus of neonatal and young adult mice,” Development, vol. 141, no. 4, pp. 773–783, 2014.

J. Heger, E. Schiegnitz, D. von Waldthausen, M. M. Anwar, H. M. Piper, and G. Euler, “Growth differentiation factor 15 acts anti-apoptotic and pro-hypertrophic in adult cardiomyocytes,” Journal of Cellular Physiology, vol. 224, no. 1, pp. 120–126, 2010.