s2fieldsofstudy: Biology Medicine

text:
Decreased mRNA expression levels of DNA methyltransferases type 1 and 3A in systemic lupus erythematosus

Objectives Systemic lupus erythematosus (SLE) is a chronic relapsing autoimmune disease characterized by the presence of autoantibodies directed against nuclear antigens and by chronic inflammation. Although the etiology of SLE remains unclear, the influence of environment factors, which is largely reflected by the epigenetic mechanisms, with DNA methylation changes in particular, is generally considered as main players in the pathogenesis of SLE. We studied DNA methyltransferases’ (DNMTs) type 1, 3A and 3B transcript levels in peripheral blood mononuclear cells from patients diagnosed with systemic lupus erythematosus and from the healthy control subjects. Furthermore, the association of DNMT1, DNMT3A, and DNMT3B mRNA levels with gender, age, and major clinical manifestations was analyzed. Methods Peripheral blood mononuclear cells (PBMCs) were isolated from 32 SLE patients and 40 healthy controls. Reverse transcription and real-time quantitative polymerase chain reaction (RT-qPCR) analyses were used to determine DNMT1, DNMT3A, and DNMT3B mRNA expression levels. Results Significantly lower DNMT1 (p = 0.015543) and DNMT3A (p = 0.003652) transcript levels in SLE patients were observed compared with healthy controls. Nevertheless, the DNMT3B mRNA expression levels were markedly lower compared with DNMT1 and DNMT3A, both in PBMCs from affected patients and those from control subjects. Furthermore, the DNMT1 transcript levels were positively correlated with SLE disease activity index (SLEDAI) (r s = 0.4087, p = 0.020224), while the DNMT3A transcript levels were negatively correlated with patients age (r s = −0.3765, p = 0.03369). Conclusions Our analyses confirmed the importance of epigenetic alterations in SLE etiology. Moreover, our results suggest that the presence of some clinical manifestations, such as phototosensitivity and arthritis, might be associated with the dysregulation of DNA methyltransferases’ mRNA expression levels.

Introduction
Systemic lupus erythematosus (SLE) is a chronic relapsing autoimmune disorder with a spectrum of clinical manifestations and outcomes [1]. SLE affects many tissues and organs (such as the skin, kidneys, joints, respiratory and nervous systems); nevertheless, etiology of this heterogeneous disorder remains incompletely described. Currently, it is established that SLE is the result of interactions between genetic, epigenetic, hormonal, and environmental factors [2][3][4][5][6]. SLE, such as many autoimmune diseases, occurs more frequently in women, and the reason for this female preponderance is suggested role of female sex hormones [7]. Recent advances in gene expression analyses, highthroughput single nucleotide polymorphism (SNP) genotyping, and association studies have identified genetic loci

Abstract
Objectives Systemic lupus erythematosus (SLE) is a chronic relapsing autoimmune disease characterized by the presence of autoantibodies directed against nuclear antigens and by chronic inflammation. Although the etiology of SLE remains unclear, the influence of environment factors, which is largely reflected by the epigenetic mechanisms, with DNA methylation changes in particular, is generally considered as main players in the pathogenesis of SLE. We studied DNA methyltransferases' (DNMTs) type 1, 3A and 3B transcript levels in peripheral blood mononuclear cells from patients diagnosed with systemic lupus erythematosus and from the healthy control subjects. Furthermore, the association of DNMT1, DNMT3A, and DNMT3B mRNA levels with gender, age, and major clinical manifestations was analyzed. Methods Peripheral blood mononuclear cells (PBMCs) were isolated from 32 SLE patients and 40 healthy controls. Reverse transcription and real-time quantitative polymerase chain reaction (RT-qPCR) analyses were used to determine DNMT1, DNMT3A, and DNMT3B mRNA expression levels.
Results Significantly lower DNMT1 (p = 0.015543) and DNMT3A (p = 0.003652) transcript levels in SLE patients were observed compared with healthy controls. Nevertheless, the DNMT3B mRNA expression levels were markedly 1 3 or genes that dictate immune abnormalities in autoimmune diseases [8,9].
Nevertheless, multiple studies have demonstrated a pivotal role of epigenetic mechanisms of gene regulation in SLE etiology. In contrast to genetic alterations, an epigenetic change is defined as a heritable change in gene expression that does not involve a change in the DNA sequence [10]. Epigenetic mechanisms play an essential role in eukaryotic gene regulation by modifying chromatin structure, which in turn modulates gene expression. There are three processes that have been most frequently implicated in epigenetic control: histone modification, DNA methylation, and microRNA expression patterns [6]. Methylation of deoxycytosine (dC) bases in CG pairs, referred to as DNA methylation, is the most common epigenetic mechanisms of gene regulation. CG pairs are found ubiquitously throughout the genome. Among all the CpGs in the human genome, 6080% are generally methylated. Less than 10% of CpGs occur in CG-dense regions that are termed CpG islands [11]. However, their transcriptionally repressive activity is generally ascribed to promoter regions [12]. DNA methylation contributes to systemic lupus erythematosus predisposition and is generally considered as key player in the pathogenesis of SLE [13]. Twin studies confirmed the importance of DNA demethylation in human lupus [14].
The addition of a methyl group to the fifth position of the cytosine pyrimidine ring, predominantly at CpG dinucleotides, is mediated by DNA methyltransferases (DNMTs). De novo methylation and maintenance methylation are two distinct processes that are required for the establishment and mitotic inheritance of tissue-specific methylation patterns (Fig. 1). Among group of the DNMTs, DNMT3A and DNMT3B catalyze de novo DNA methylation, and DNMT1 mediates the maintenance of DNA methylation [11]. DNMT1 is the maintenance DNA methylation enzyme, recognizing hemimethylated cytosines during the S phase of the cell cycle and copying these marks onto the nascent strand during replication [15,16]. Studies with the embryonic stem cells (ES cells) with inactivated DNMT3A and DNMT3B genes by gene targeting, demonstrated blocks de novo methylation in ES cells and early embryos [17]. These results indicate that both DNMT3A and DNMT3B are required for genome-wide de novo methylation and are essential for mammalian development.
We studied DNMT1, DNMT3A, and DNMT3B transcript levels in peripheral blood mononuclear cells (PBMCs) from 32 patients diagnosed with SLE and from 40 individuals as a control group.

Human subjects
Thirty-two peripheral blood samples were obtained from patients diagnosed with SLE at the Department of Rheumatology and Internal Diseases in Poznan, Poland (Table 1), and 40 samples from the control group (40 females; median age = 30, range 19-47, mean age ± SD = 30.8 ± 8.6) were collected at the Regional Blood Donation and Blood Treatment Center in Poznan, Poland. The healthy control Fig. 1 Maintenance (a) and de novo DNMTs (b) methylate DNA. DNMT1 binds methyl groups to the hemimethylated DNA during replication, whereas DNMT3A and DNMT3B can add methyl groups to CpG dinucleotides of unmethylated DNA. From Luczak and Jagodziński [23] subjects were selected from healthy blood donors without any rheumatologic conditions. At the time of blood donation, the median and mean age of the patients were 36 (range 19-74) and 37.9 ± 14.4 years, respectively. Based on the SLE disease activity index (SLEDAI), SLE patients were divided into 12 inactive (SLEDAI <6) and 20 active (SLEDAI ≥6) cases. Peripheral blood samples were collected from all the patients before they took any immunosuppressive drug, glucocorticoid or cytotoxic drugs to exclude the influence of drugs. The study procedures were approved by the Local Ethical Committee of Poznań University of Medical Sciences.

Isolation of PBMCs
Human peripheral blood mononuclear cells were isolated using Ficoll density gradient centrifugation method. Ficoll is a neutral, high-mass, branched polysaccharide that simply dissolves in aqueous solutions [18]. Blood (3 mL) was gently layered on top of an equal volume of Ficoll® (Sigma) solution (without mixing the two layers) in a 15 mL conical tube. The samples were centrifuged at 600×g for 50 min at room temperature whit the brake in the off position. PBMCs are retained at the interface between the Ficoll and plasma layers. The layer containing the mononuclear cells was harvested in 1.5 mL microcentrifuge tubes. In the next step, cells were washed in phosphate buffered saline (PBS) supplemented with 2 mM EDTA. Finally, after centrifugation at 250×g for 10 min, cells were resuspended in TRIzol® Reagent (Invitrogen, USA) for downstream applications.

Reverse transcription and real-time quantitative polymerase chain reaction (RT-qPCR) analyses
Total RNA from PBMCs was isolated according to the method published by Chomczyński and Sacchi [19]. RNA integrity was determined by denaturing agarose gel electrophoresis, and then, the RNA was quantified by measuring the optical density (OD) at 260 nm. RNA samples were treated with DNase I and reverse-transcribed into cDNA using Moloney Murine Leukemia Virus (M-MLV) Reverse Transcriptase from Invitrogen, Life Technologies (Grand Island, NY), according to the manufacturer's protocol. RT-qPCR was conducted in a Light Cycler®480 Real-Time PCR System, Roche Diagnostics GmbH (Mannheim, Germany) with SYBR Green I as the detection dye. The target cDNA was quantified by the relative quantification method using a calibrator for patient or control PBMCs. For the calibrator, 1 μl of cDNA from all samples were mixed together, and successive dilutions were used to create a standard curve as described in the Relative Quantification Manual Roche Diagnostics GmbH (Mannheim, Germany). For relative quantification, we applied the E-Method algorithm. The DNMT1, DNMT3A, and DNMT3B transcript levels in each sample were standardized to the porphobilinogen deaminase (PBGD) transcript level as an internal control. The DNMT1, DNMT3A, and DNMT3B transcript levels in PBMCs from the patients with SLE and the controls were expressed as a multiplicity of the cDNA concentration in the calibrator. For the amplification reactions, 1 μL of total (20 μl) cDNA solution was added to 9 μL of 5× LightCycler® 480 SYBR Green I Master from Roche Diagnostics GmbH (Mannheim, Germany) with primers ( Table 2). Agarose gel electrophoresis was applied to confirm the specificity of the amplified products.

Statistical analysis
The normality of the observed patient data distribution was assessed by the Shapiro-Wilk test, followed by the Mann-Whitney U test to identify statistically significant differences between the compared mean values. Correlations were calculated using Spearman's rank correlation coefficient (r s ). p values <0.05 were considered to be statistically significant. Statistical analyses were performed using the STATISTICA 12 software.

Results
In the present study, employing RT-qPCR to compare the mRNA levels, DNMT1, DNMT3A, and DNMT3B transcripts in peripheral blood mononuclear cells from patients with SLE and healthy individuals were identified. Nevertheless, the DNMT3B transcript levels were markedly lower compared with DNMT1 and DNMT3A, both in PBMCs from affected patients (p < 0.00001 for DNMT1 and DNMT3A) and those from control subjects (p < 0.00001 for both enzymes also; Fig. 2). Significantly lower DNMT1 transcript expression (p = 0.015543) was observed in the 32 SLE patients than in the healthy controls. DNMT3A transcript levels also decreased significantly (p = 0.003652) in patients diagnosed with SLE compared with the controls. SLE patients and controls showed similar mRNA levels of DNMT3B (p = 0.852599). We also analyzed the relationships between DNMT1, DNMT3A, and DNMT3B mRNA expression levels and gender, age, and major clinical manifestations (listed in Table 1). Regarding the correlation of mRNA expression levels among SLE patients, DNMT1 transcript levels were positively correlated with SLE disease activity index (SLEDAI) (r s = 0.4087, p = 0.020224; Fig. 3a). Interestingly, DNMT1 mRNA levels in active (SLEDAI ≥6) SLE patients were slightly higher compared with inactive (SLE-DAI <6) SLE group; nevertheless, it was not statistically significant (p = 0.054007). Furthermore, the DNMT3A transcript levels were negatively correlated with patients age (r s = −0.3765, p = 0.03369; Fig. 3b). This result suggests a lower mRNA expression levels of DNMT3A in older group of SLE patients (age >40); however, there was no statistically significant difference in the expression of DNMT3A mRNA among the different age groups (p = 0.076547). Substantial increase of DNMT3A mRNA amount in PBMCs (p = 0.023808) was observed in the group of patients with phototosensitivity (18 patients, 56.3%; Fig. 4a). Furthermore, individuals with arthritis (9 patients, 28.1%) were found to have significantly lower levels of DNMT3B mRNA levels (p = 0.029297) than patients without arthritis (Fig. 4b).

Discussion
Genetic and epigenetic alterations unquestionably play a pivotal role in etiology of systemic lupus erythematosus (SLE). Studies of epigenetic aberrations in lupus patients have primarily focused on DNA methylation and various covalent histone modifications. DNA methylation is an epigenetic mark that is critical in determining chromatin accessibility and regulating gene expression. This epigenetic mechanism most frequently occurs at the fifth carbon of the pyrimidine ring in cytosine residues, primarily located in cytosine-guanosine dinucleotides (CpG dinucleotides). To this day have been described different patterns by which this epigenetic modification may affect chromatin accessibility. DNA methylation in the promoter regions is associated with gene silencing, thus linking DNA methylation to chromatin inaccessibility and gene suppression [20]. Interestingly, Hughes et al. [12] demonstrated that DNA methylation in gene promoter regions is not always a repressive epigenetic mark. Nevertheless, recent studies have also focused on the roles of DNA methylation in gene bodies and intergenic regions in enhancing gene expression [21,22]. The mammalian DNA cytosine-5-methyltransferases' (DNMTs) family comprises DNMT1, DNMT2, DNMT3A, DNMT3B, and DNMT3L; however, DNMT3L is primarily  Total RNA was reverse-transcribed, and cDNAs were investigated by RT-qPCR relative quantification analysis. The DNMT1, DNMT3A, and DNMT3B mRNA levels were corrected by PBGD level. The amounts of DNMT1, DNMT3A, and DNMT3B mRNA were expressed as the decimal logarithm of multiples of these cDNA copies in the calibrator restricted to early embryogenesis, and does not play a major role [11,16]. DNA methylation is established by the combined action of three DNMTs (DNMT2 functions to methylate RNA): DNMT1 is the maintenance methyltransferase and binds methyl groups to the hemimethylated DNA during replication, whereas DNMT3A and DNMT3B exhibit de novo methyltransferases' activity and add methyl groups to CpG dinucleotides of unmethylated DNA to create new patterns of methylation [23,24]. Thus, we analyzed the changes in transcript levels of DNMT1, DNMT3A, and DNMT3B in the whole PBMC population. DNA methylation changes are closely related to the pathogenesis of SLE. Many studies have shown that abnormal DNA hypomethylation in some genes of CD4+ T cells can result in creation of autoreactive T cells and autoantibody generation. The most important methylationsensitive T-cell genes include inter alia CD11a (encoded by gene ITGAL), perforin 1 (PRF1), CD70 (TNFSF7), CD40 ligand (TNFSF5), or killer-cell immunoglobulinlike receptors (KIR2DL4) [15,[24][25][26][27]. Other studies indicated that demethylation of inflammatory cytokine genes from interleukin family in CD4+ T cells might participate in the progression of SLE [28]. DNA methylation changes in regulatory regions of mentioned genes may be the result of action various factors, such as regulatory factor X 1 (RFX1) [29], overexpression of some microRNA [30][31][32], or long non-coding RNAs (lncRNAs) [33], which through interacting with DNMTs affects DNA methylation at distal target promoters. Other research found that Ras-mitogenactivated protein kinase (MAPK) and extracellular receptor associated kinase (ERK) pathway were involved in DNA hypomethylation by down-regulating DNMT activity in SLE [34,35]. To confirm the importance of DNA hypomethylation in the progression of SLE, in recent years, few laboratories performed high-throughput genome-scale DNA methylation analysis and confirmed that the methylation level of many genes contributed to the development of diversified manifestations in SLE [14,[36][37][38]. Furthermore, by genome-scale DNA methylation analysis, Chung et al. found hypomethylation of CpG sites within genes from different pathways, which were involved in the production of autoantibodies to nuclear antigens in SLE [39].
In our study, using RT-qPCR analysis, we found decreased expression of DNMT1 and DNMT3A mRNA levels in SLE patients compared with the healthy individuals. As a consequence, and based on our results, we made the assumption that PBMCs from patients with SLE may be characterized by a global DNA hypomethylation. Other investigators demonstrated that both entire pool of PBMCs [40] and isolated T cells [41][42][43] from patients with SLE had a global DNA hypomethylation. Balada et al. [42] also demonstrated that CD4+ T cells from SLE patients had a low DNA methylcytosine content. Nevertheless, in contrast to our results, authors have shown similar mRNA levels of DNMT1, DNMT3A, and DMT3B in patients and control groups. It should be pointed out clearly that these authors used only purified CD4+ T cells from the entire pool of mononuclear cells. Overall, all enzymes reflected a wide range of variability among individuals, especially DNMT1 and DNMT3A. However, authors in other studies found that T cells [35] or PBMCs [44] from patients with lupus have exhibited a reduced DNMT1 mRNA levels. Some authors suggest that a defect in DNMT1 may be the primary reason of abnormal DNA methylation in CD4+ T cells from lupus patients [25]. Completely different results were achieved by Liu laboratory, and authors demonstrated significantly increased DNMT1 mRNA expression in SLE patients compared with the controls [40]. Other investigators [43,45] described significantly higher mRNA levels of other enzymes (MBD1, MBD3, and MBD4), involved in the DNA methylation process, in patients with lupus. Therefore, these investigations suggest that the global DNA methylation may be dependent on multiple factors, such as DNMT mRNA levels, DNMT activity, DNMT protein levels, and transcript levels of other enzymes involved in the DNA methylation process. Nevertheless, our results confirmed the importance of epigenetic alterations in SLE etiology. Decreased expression of the DNMT1 and DNMT3A might be associated with generation of autoreactive T cells and autoantibody production. According to our results, in Balada studies [42], authors observed higher transcript levels of DNMT1 (moreover also for the DNMT3A) in active SLE patients. In the present study, we demonstrated markedly lower transcript levels of DNMT3B in PBMCs from SLE patients and those from control group-other studies also confirmed these observations [32,42]. These results suggest that DNMT3B seems to be transcribed at low levels in PBMCs. Therefore, we may postulate that DNMT3A is the main enzyme which exhibits de novo methyltransferases' activity in PBMCs both from affected patients and those from control subjects to create new patterns of methylation. Subsequent studies of Balada laboratory [27] also demonstrated that SLE patients had significantly less CD4+ T-cell DNA deoxymethylocytosine content than controls. As shown in this manuscript, ITGAL and PRF1 mRNA levels were directly and strongly correlated with the transcript levels of three DNMTs playing the lead role in DNA methylation.
In the present study, we also found positive correlation between DNMT1 transcript levels and SLE disease activity index (SLEDAI). Interestingly, our results suggest slightly higher mRNA levels of DNMT1 in group of patients with active (SLEDAI ≥6) SLE. The emerging discrepancy may be associated, as suggested by some [44] investigators, with corticosteroid treatment. Ogasawara et al. have reported that the levels of DNMT1 mRNA by peripheral blood mononuclear cells from patients with SLE were increased after corticosteroid treatment [44]. Moreover, previously published data support the hypothesis that cells respond to pharmacological or dietetical inhibition of methylation by induction of methyltransferase activity [46,47]. Some authors [48] suggested that the DNMT activity is itself regulated, in part, by DNA methylation status, which represents a feedback mechanism. Investigators have found a regulatory region in murine dnmt1 that seems to act as a sensor of the DNA methylation capacity of the cell. Furthermore, we observed an inverse correlation between the DNMT3A transcript levels and patients age. Whereas Zhang et al. [49] also found that the levels of DNMT1 and DNMT3A decreased with aging and that this change correlated with the hypomethylation of sequences flanking the ITGAL promoter. Other studies have shown that in DNA from aged subjects (65-90 years) compared with young subjects (20-35 years) is significantly decreased global level of methylation suggesting that age-associated hypomethylation of the DNA may be the cause of its increased immunogenicity. This change may thus be another mechanism that may contribute to the increase in age-associated chronic inflammation and autoimmunity. Moreover, delivery of DNA from aged compared with young subjects into PBMCs stimulated a significantly greater secretion of an inflammatory cytokine (IFN-α) and costimulatory markers CD80 and CD86 [50]. Therefore, we may postulate that a decrease of DNMTs expression during adulthood may be the pathway to development of autoimmunity with aging. Our results suggest also that the presence of some clinical manifestations, such as phototosensitivity and arthritis, might be associated with the dysregulation of DNA methyltransferases mRNA expression levels. As reviewed by Medlin et al. [51] in pooled analysis of SLE patients, most cutaneous manifestations (including phototosensitivity) were less prevalent in the late-onset SLE patients. Studies with Xeroderma pigmentosum (genetic disease characterized by hypersensitivity to UV exposure, associated with numerous skin abnormalities) skin cells indicate enormous importance of CpG methylation on frequency of targeted mutagenesis (TM) [52]. The distribution of TM events within the amplicon population was strongly biased toward demethylated sequences. Increase of TM frequency was observed when the DNMT1 gene was knocked down using specific siRNA. In addition, no induction of targeted mutagenesis after 5-aza-dC treatment was observed in the cells. Obtained by us results indicate slightly higher DNMT3A transcript levels, which may be associated with cells respond to pharmacological or dietetical inhibition of DNMTs activity. Less significance seems to have changes in the DNMT3B mRNA level changes associated with arthritis, because according to our results, this enzyme plays only a supporting role in methylation in PBMCs.
In our study, we analyzed the changes in transcript levels of DNMT1, DNMT3A, and DNMT3B in the whole PBMCs population. Note, mRNA levels in each group of immune cells may differ from the overall results obtained for PBMCs. For example, our results better reflect epigenetic changes in CD4 T cells (represent range of 25-60% of PBMC) than in B cells (up to 15% of PBMC). In humans, the frequencies of these populations vary across individuals, and also cell composition might be different in healthy controls and patients. The main limitation of our study is the lack of correlation between protein and mRNA levels. Keeping in mind the small amount of samples, we decided to investigate only DNMT1, DNMT3A, and DNMT3B mRNA levels.

Conclusion
Our analyses confirmed the importance of epigenetic alterations in SLE etiology. Decreased expression of the two DNA cytosine-5-methyltransferases (DNMT1 and DNMT3A) might be associated with generation of autoreactive T cells and autoantibody production. We have shown that DNMT3A is the main enzyme which exhibits de novo methyltransferases activity in PBMCs both from affected patients and those from control subjects. In addition, our result can indicate the way by which it is achieved DNA hypomethylation in some specific genes in SLE pathogenesis.


extfieldsofstudy: Biology Medicine

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Nucleosomal organization and DNA base composition patterns.

Nucleosomes are the basic units of chromatin. They compact the genome inside the nucleus and regulate the access of proteins to DNA. In the yeast genome, most nucleosomes occupy well-defined positions, which are maintained under many different physiological situations and genetic backgrounds. Although several short sequence elements have been described that favor or reduce the affinity between histones and DNA, the extent to which the DNA sequence affects nucleosome positioning in the genomic context remains unclear. Recent analyses indicate that the base composition pattern of mononucleosomal DNA differs among species, and that the same sequence elements have a different impact on nucleosome positioning in different genomes despite the high level of phylogenetic conservation of histones. These studies have also shown that the DNA sequence contributes to nucleosome positioning to the point that it is possible to design synthetic DNA molecules capable of generating regular and species-specific nucleosomal patterns in vivo.

Introduction
Eukaryotic genomes are packaged into chromatin to be confined within the nucleus. The basic units of chromatin are the nucleosomes, histones octamers wrapped by »1.7 turns of DNA that accommodate 147 base pairs (bp). Genome-wide maps of several yeasts species have revealed that most nucleosomes occupy well-defined and stable positions along the chromosomes during the cell cycle and under different physiological conditions. [1][2][3] Nucleosome positioning results from the combined contribution of chromatin remodelers, transcription factors, and the DNA sequence. Remodelers facilitate the sliding, eviction or exchange of nucleosomes using ATP hydrolysis, and the depletion of some of them, such as hrp3 in Schizosaccharomyces pombe or ISW1 and CHD1 in Saccharomyces cerevisiae, can cause widespread alterations in nucleosomal organization. [4][5][6] Transcription factors can compete with histones for the access to specific locations in DNA to generate nucleosome depleted regions (NDRs). 2,7,8 The contribution of the DNA sequence to nucleosome positioning in vivo remains unclear. Based on genome-wide in vitro chromatin assembly, it has been suggested that most nucleosomes are positioned according to a universal code specified by the DNA sequence. 9,10 In contrast to this proposal, the statistical positioning model proposes that regular nucleosomal arrays are passively propagated from physical barriers bound to DNA. 11 According to this model, the contribution of the DNA sequence would be to determine the location of such barriers, which could coincide with protein complexes bound to gene promoters or other DNA binding proteins. While both models may contribute to nucleosome positioning in specific genomic regions, neither of them can sufficiently account for the positioning pattern found in vivo.
Considering that histones are among the most conserved proteins in evolution, if nucleosome positioning was entirely independent of the underlying sequence, it would be expected that the insertion of exogenous DNA fragments into a host genome would adopt the endogenous nucleosomal pattern.  12 Nucleosome positioning of Yeast Artificial Chromosomes (YACs) containing genomic DNA from Kluyveromyces lactis, Kluyveromyces waltii and Debaryomyces hansenii differs from that of their original genomes when harbored by S. cerevisiae, and do not adopt the endogenous S. cerevisiae pattern either. 13 This phenomenon is also observed between closely related species as Saccharomyces paradoxus and S. cerevisiae, 14 and even between orthologous genes like the ura4 gene in S. pombe, Schizosaccharomyces octosporus and Schizosaccharomyces japonicus. The pattern of nucleosome positioning generated by the ura4 gene from S. octosporus inserted into the S. pombe genome is more similar to the endogenous profile than that of the S. japonicus ura4 gene, which correlates with S. japonicus being more distantly related to S. pombe than S. octosporus. 15

Base composition and nucleosomal patterns
It has long been known that different DNA sequence elements have different affinities to nucleosomes. For example, the 5S rRNA gene has a strong positioning potential in vitro and in vivo. 16,17 By contrast, poly (dA:dT) tracts are refractory to nucleosome formation due to difficulty in bending around the histone octamer. They colocalize with sites of lower nucleosomal occupancy in S. cerevisiae (Fig. 1A) and are overrepresented in NDRs at gene promoters ( Fig. 1B), where they facilitate the access of transcription factors to their binding sites. [18][19][20][21] In fact, 72.5% of all NDRs in S. cerevisiae include poly(dA:dT) elements 7 bp long (Fig. 1C). This situation is not universal, however, since in S. pombe nucleosome occupancy is not reduced over the same elements ( Fig. 1A) and they are not overrepresented at promoter NDRs relative to their average genomic distribution 1 (Fig. 1B). In contrast with the situation in S. cerevisiae, only 18% of all NDRs include poly(dA:dT) elements 7 bp long in S. pombe (Fig. 1C). In addition, high-resolution studies have shown that the ACT content oscillates in phase with the occupancy profile in S. pombe, while in S. cerevisiae it peaks at linker regions. [22][23][24][25] Despite the differences among species, several laboratories have reported a periodic 10 bp pattern in the distribution of AT-and GC-rich dinucleotides in aggregated profiles of mononucleosomal DNA. This feature favors the bendability of DNA around the histone core and has been described in different species. 9,[26][27][28] Many studies have addressed the potential of DNA sequences to form nucleosomes using in vitro chromatin assembly under controlled biochemical conditions (see for example refs. [28][29][30]. These approaches have uncovered important properties of the DNA-histone interactions, but do not always mimic the nucleosomal patterns found in the genomic context. 31,32 To explore the connection between the DNA sequence and nucleosome positioning in vivo, we analyzed the distribution of the 4 nucleotides within 30,000 to 40,000 sequences of mononucleosomal DNA of S. cerevisiae and 3 species of Schizosaccharomyces, 25 and found they followed well-defined patterns, showing a higher content of adenine at the 5' end and thymine at the 3' end of each strand of mononucleosomal DNA. This asymmetric distribution was also observed-although to a lesser extent-between cytosine and guanine and was present in transcribed and non-transcribed regions. We have called these patterns nucleosomal signatures and they are different among species. In the case of coding regions (ORFs), nucleosomal signatures determine a species-specific periodicity in the distribution of amino acids that establishes an unanticipated connection between the position of individual codons around the nucleosome and protein composition, which has important consequences for gene evolution. 25,33,34 Nucleosomal signatures contain positioning information These observations raised the question of whether nucleosomal signatures could represent a molecular footprint caused by the stable association between nucleosomes and the DNA molecule over evolutionary timescales, 33 or whether they could contribute to the positioning of nucleosomes in the genome.
To explore this possibility, we randomized the sequence of several mononucleosomal DNA regions and used them to replace the native sequences within the genome. It was observed that the regular wild-type nucleosomal pattern was severely disturbed in regions that coincided precisely with the modified sequences. The same result was obtained when the modification of the sequence was limited to the substitution of the wild-type codons for their synonymous codons in the ORFs. This effect was not dependent on transcription since it was equally detectable in transcribed and non-transcribed regions, and suggested the existence of some type of information required for positioning that had been lost in the modified sequences.
To more directly test whether the nucleosomal signatures contributed to nucleosome positioning, we generated position-specific weight matrices to extract the information contained within them to design artificial non-coding sequences to evaluate their potential to position nucleosomes. 15 Strikingly, the insertion of artificial sequences based on the nucleosomal signature found in the S. pombe genome into its own genome led to the positioning of nucleosomes in the predicted positions. The same sequence, however, did not position nucleosomes in S. cerevisiae. Conversely, the artificial sequence designed according to the S. cerevisiae signature specified a strictly regular nucleosomal array in S. cerevisiae, but failed to do so in S. pombe.
The information present in nucleosomal signatures is degenerated and, in principle, would allow the design of thousands of different sequences with a similar positioning potential in vivo. This flexibility opened the possibility of incorporating this information into coding regions through the use of synonymous codons. Also, this would allow modifying heterologous ORFs to mimic the nucleosomal organization of the host genome to overcome the deficient positioning of exogenous sequences, as discussed above. We tested this possibility by re-designing the ORFs of the ura4 gene of S. octosporus and S. japonicus based on the nucleosomal signatures of S. pombe without modifying their native coding potential. Nucleosome mapping showed that the two designer versions were capable of positioning nucleosomes in S. pombe with even a sharper profile than the endogenous ura4 ORF. Likewise, two customized versions of the bacterial gene kan r ¡a widely used marker for plasmids that confers resistance to geneticin¡were used using the same strategy and generated regular nucleosomal arrays in S. pombe and S. cerevisiae that were not maintained when used interchangeably. These results indicated that nucleosomal signatures contain information that can direct nucleosome positioning in a species-specific manner, 15 and open the possibility of using them to engineer prokaryotic and eukaryotic genes to adopt the specific nucleosomal organization of the host organism. Their possible applications will be discussed below.

Possible applications of nucleosomal signatures
The DNA molecule contains multiple layers of information that have been extensively manipulated for biotechnological purposes. This includes optimization of genes to improve their heterologous expression through the incorporation of the codon bias of the host genome or the avoidance of cryptic splice-sites and some RNA secondary structures. 35 Our results show that nucleosomal signatures represent an additional layer of information that contributes to the species-specific organization of chromatin at its most basic level. In the case of eukaryotic hosts, the ability to reproduce the endogenous nucleosomal pattern could improve gene expression and to avoid undesired consequences of the lack of positioning such as antisense transcription and cryptic promoter formation. 13 The information contained in nucleosomal signatures could also be of interest in synthetic biology and, more specifically, in the expanding field of genome design. 36 In this respect, the Sc2.0 international consortium is currently building a synthetic version of the S.cerevisiae genome, with some chromosomes already completed. 37,38 An important question currently being addressed is how these synthetic chromosomes are organized in the nucleus. 39 The close relationship between DNA sequence and nucleosome positioning discussed above suggests that small changes introduced in the sequence of synthetic chromosomes will probably have an impact on nucleosome positioning. Given that differences in nucleosome positioning or in their affinity for DNA have an effect on transcription, 40,41 DNA replication, 42,43 and recombination 44 it is possible that the feasibility of targeting nucleosomes to specific positions through the incorporation of nucleosomal signatures into DNA sequences could contribute to improve the functionality of designer chromosomes.

Disclosure of potential conflicts of interest
No potential conflicts of interest were disclosed.

Funding
This work was funded by grant BFU2014-52143-P from the Spanish Ministerio de Econom ıa y Competitividad (MINECO).


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Inhibitory effects of Stichopus japonicus extract on melanogenesis of mouse cells via ERK phosphorylation

Stichopus japonicus has been used as a folk medicine and as an ingredient in traditional food in East Asian countries. In recent years, the bioactive compounds found in S. japonicus have been reported to possess efficacy in wound healing and may be of potential use in the cosmeceutical, pharmaceutical and biomedical industries. Although the components and their functions require further investigation, S. japonicus extracts exhibit anti-inflammatory properties, and may be used for cancer prevention and treatment. Although several reports have examined different aspects of S. japonicus, the effects of S. japonicus extract on melanogenesis in the skin has not been reported to date. Therefore the present study aimed to investigate the effects of S. japonicus extract on melanogenesis. Treatment with a mixture of S. japonicus extracts (MSCE) reduced melanin synthesis and tyrosinase (TYR) activity in mouse melanocyte cells lines, B16F10 and Melan-A. In addition, MSCE treatment reduced the protein expression levels of TYR, tyrosinase-related protein-1 and tyrosinase-related protein-2. The reduced protein levels may be the result of decreased microphthalmia-associated transcription factor (MITF) expression, which is an important regulator of melanogenesis. The reduced expression level of MITF was associated with delayed phosphorylation of extracellular signal-regulated kinase (ERK) induced by MSCE treatment. A specific MEK inhibitor, PD98059, significantly blocked MSCE-mediated inhibition of melanin synthesis. In conclusion, these results indicate that MSCE may be useful as a potential skin-whitening compound in the skin medical industry.

Introduction
Melanocytes are melanin-producing cells that are located in the basal layer of the skin epidermis. Melanogenesis is the physiological process that mediates photoprotection of the skin from ultraviolet (UV) radiation-induced injury by producing melanin in the skin and hair (1). However, overexposure to UV radiation may result in hyperpigmentation disorders, including melasma, freckles, lentigo, skin wrinkles and skin cancers, all of which are of medical and cosmetic interest (2)(3)(4).
Melanogenesis is regulated by melanogenic enzymes, including tyrosinase (TYR), tyrosinase-related protein 1 (TRP-1), and tyrosinase related protein 2 (TRP-2) (5). TYR is the predominant enzyme that catalyzes the rate-limiting phase of melanogenesis, and the inhibition of this enzyme is a typical method used to improve pigmentation (6). TYR is crucial for the regulation of melanin synthesis through the hydroxylation of tyrosine to 3,4-dihydroxyphenylalanine (DOPA) and the oxidation of DOPA to dopaquinone (7). Members of the tyrosinase (TYR) gene family (which includes TYR, TRP1 and TRP2) that are responsible for melanin synthesis are transcriptionally regulated by microphthalmia-associated transcription factor (MITF), which regulates differentiation, proliferation and pigmentation of melanocytes. In addition, mutations in MITF can lead to the abnormal synthesis of melanin, which results in hyperpigmentation of the skin and hair (8). For this reason, compounds that inhibit the expression of MITF may be useful as depigmentation agents (9).
It is well known that various signaling pathways are involved in regulating melanogenesis. Phosphorylation of the mitogen-activated protein kinase (MAPK) signaling pathways lead to a reduction of melanin synthesis in mouse melanocytes. Several studies suggested that activation/phosphorylation of the extracellular signal-regulated kinase (ERK) and c-Jun N-terminal kinase (JNK) signaling pathways results in the inhibition of melanogenesis (10,11). This effect has been attributed to the phosphorylation of MITF at serine 73, which results in MITF ubiquitination and degradation (12). Thus, the activation of ERK and JNK signaling inhibits melanogenesis by reducing MITF expression and TYR activity.
A number of melanin synthesis inhibitors, including kojic acid and arbutin, have been the focus of previous studies and are currently being used as functional bio-cutaneous compounds for whitening of pigmentary disorders such as melasma, dark circles and post-inflammatory hyperpigmentation (13). Compounds with possible applications in the cosmetic industry have been the target of ongoing research and attention. However, the use of melanogenesis inhibitors is heavily regulated owing to their clinical side effects, and only a few of them (such as arbutin and kojic acid) are currently used commercially (14). Therefore, it would be beneficial to identify additional effective compounds that may be able to modulate melanogenesis for use in the medical and cosmetic industry.
The Korean red sea cucumber Stichopus japonicus is a marine echinoderm of the Holothuroidea family; it is consumed in East Asian countries, such as China, Indonesia, Korea and Japan. For centuries, it has been used as a remedy for inflammation and to treat illnesses or infections from viral and bacterial pathogens (15). S. japonicus has also been used as an effective remedy for treating various internal and external wounds, including athlete's foot. Several studies have demonstrated that S. japonicus extracts exhibit a number of biological properties, such as antioxidant, antifungal, and immunomodulatory activity (16)(17)(18). These extracts have been revealed to contain lectins, peptides, minerals, vitamins and various other molecules, including chondroitin sulfates, glycosaminoglycan and polysaccharides. These compounds may be responsible for the powerful wound-repairing abilities, and anti-inflammatory, antifungal, and antiviral properties (19). Based on these data, S. japonicus extracts may be an excellent candidate for inclusion in cosmeceutical and skin medical compounds for treating skin pigmentation disorders including melasma and post-inflammatory hyperpigmentation (PIH).
However, depigmentation via inhibition of TYR and melanin synthesis, and the associated molecular mechanism of the mixture of S. japonicus extracts (MSCE), have not been examined as a candidate for a skin topical agent to improve hyperpigmentation. To investigate the mechanistic action of MSCE in melanin synthesis, the effects of MSCE on melanin synthesis and TYR expression was investigated. The results suggested that MSCE treatment inhibited melanogenesis through the ERK signaling pathway in mouse melanocyte cells.

Materials and methods
Sample preparation and extraction procedure. Over 1,000 live specimens of S. japonicus (average body weight 180 g) were obtained from fishermen on the Korean islands of Sochong and Daechong. Fresh S. japonicus specimens were divided into the visceral organs and the body, and were rinsed with clean water. Subsequently, the body was dried using traditional salting and drying procedures, which involved drying for 1 day in the sea breeze, and the visceral organs were frozen at -80 to-90˚C. The dried S. japonicus bodies, which were prepared at Catholic Kwandong University, International St. Mary's Hospital (Incheon, Korea), were ground using a blender and 150 g of the resulting powder was dissolved in 2 liters 65% ethanol for 2 h at room temperature with continual mixing. The solution was filtered through cotton and underwent reflux extraction using a COSMOS-660 Universal Vacuum Extractor (Kyungseo Machine Co., Incheon, Korea). The extract was concentrated using an EYELA N-12 Vacuum Evaporator connected to an EYELA CA-1112 Low-Temperature Water Circulator (Tokyo Rikakikai Co., Ltd., Tokyo, Japan) prior to freeze-drying with a TFD-100 Freeze Dryer (ilShinBioBase Co., Ltd., Gyeonggi-do, Korea) and powdered. Cell culture. B16F10 mouse melanoma cells were purchased from the American Type Culture Collection (Manassas, VA, USA). Cells were cultured in DMEM containing 10% FBS and 1% P/S in 5% CO 2 at 37˚C. Melan-A immortalized mouse melanocytes were obtained from Professor Dorothy C. Bennett (St. George's, University of London, London, UK) (20) and were cultured in RPMI-1640 medium containing 10% FBS, 1% P/S, and 200 nM PMA in 10% CO 2 at 37˚C.
Cell viability assay. The mouse cells were seeded (1x10 4 cells/well) in 96-well plates and incubated at 37˚C. Following a 24 h incubation, the cells were washed with DPBS (WelGene, Inc., Daegu, Korea) and replaced with DMEM (B16F10 cells) or RPMI1640 (Melan-A cells), containing MSCE diluted to various concentrations at 0-100%. Following 24 h at 37˚C, the cells were washed with DPBS, and DMEM (B16F10 cells) or RPMI1640 (Melan-A cells) containing 10% CCK-8 solution was added. The cells were then incubated at room temperature and the absorbance was measured at 450 nm using a microplate reader (SpectraMax 340; Molecular Devices, LLC, Sunnyvale, CA, USA).
Mushroom TYR activity assay. A mushroom TYR activity assay was assessed by measuring DOPA oxidase activity using a slightly modified experimental protocol from a previous study (21). Briefly, 95 µl of 0.1 M sodium phosphate buffer (pH 6.5) containing the indicated concentrations of kojic acid (50 µM) and MSCE, and 20 µl of mushroom TYR (1,000 U/ml) were combined in each well, and 20 µl of 5 mM l-DOPA was then added. The absorbance was measured at 475 nm every 10 min for 1 h using a microplate reader (SpectraMax 340; Molecular Devices, LLC, Sunnyvale, CA, USA).
Melanin assay. B16F10 cells characteristically release melanin, which was measured with slight modifications to a previously described protocol (22). Briefly, cells were seeded (1x10 5 cells/well) in 6-well plates. Following 24 h at 37˚C, the plates were washed with DPBS and the media was replaced with phenol red-free DMEM containing α-MSH (1 µM), or PD98059 (10 µM) for 30 min at 37˚C followed by α-MSH and MSCE treatment as aforementioned. The cells were subsequently incubated for 3 days. Absorbance was measured in the cell culture supernatant at 405 nm using a microplate reader (SpectraMax 340; Molecular Devices, LLC, Sunnyvale, CA, USA). PTU is an inhibitor of melanin synthesis, and this compound was employed as a positive control; BF16F10 cells were treated with PTU (50 µM) for 3 days at 37˚C in place of MSCE.
Melan-A cells were seeded (5x10 5 cells/well) in 24-well plates. Following 24 h incubation, the plates were washed with DPBS, and then RPMI1640 containing the indicated concentrations of MSCE or PD98059 (pretreated for 30 min at 37˚C, prior to MSCE treatment) was added. The plates were subsequently incubated at 37˚C for 3 days. Cells were lysed in 110 µl of 1 N NaOH at 55˚C for 15 min, and the absorbance was measured at 470 nm using a microplate reader (SpectraMax 340; Molecular Devices, LLC, Sunnyvale, CA, USA). All results were normalized to the total protein concentration of the cell pellet using a Bicinchoninic Acid Assay kit (Pierce; Thermo Fisher Scientific, Inc.).
Immunocytochemistry. Cells were seeded (1x10 5 cells/well) onto glass coverslips pre-coated with poly-l-lysine (Sigma-Aldrich; Merck KGaA) and incubated for 24 h at 4˚C. Slides were fixed with 4% paraformaldehyde for 15 min at room temperature. Following washing with PBS, cells were treated with 0.01% Triton X-100 (Sigma-Aldrich; Merck KGaA) and then blocked with 2% bovine serum albumin (Merck KGaA) in TBS-T for 1 h at room temperature. The cells were incubated with an anti-TYR antibody (1:100) at 4˚C overnight. Following washing with TBS-T + 0.1% Tween-20 buffer, cells were incubated for 3 h at 4˚C with goat anti-rabbit IgG-fluorescein isothiocyanate secondary antibodies (1:1,000; SC-2012, Santa Cruz Biotechnology, Inc.) and mounted with fluorescent mounting medium containing DAPI (Golden Bridge International, Inc., Bothell, WA, USA). Cell morphology was observed using a FluoView FV10i fluorescence microscope and a DP70 Digital Microscope Camera (both from Olympus Corporation, Tokyo, Japan). Images were processed using the proprietary DP70 Controller software (Ver.03.03; Olympus Corporation).
Statistical analysis. Statistical analyses were performed using SPSS 18.0 (SPSS, Inc., Chicago, IL, USA). There were three replicates for each of the data measurements. Results are presented as the mean ± standard deviation. Data were analyzed by one-way analysis of variance, followed by Tukey's multiple comparison tests. P<0.05 was considered to indicate a statistically significant difference.

Results
Effects of MSCE on mouse melanocyte cell viability. First, a CCK-8 assay was performed to evaluate the cytotoxicity of MSCE on B16F10 mouse melanoma cells and Melan-A normal mouse melanocytes. Cells were treated with MSCE at a concentration range of 0-100%. As demonstrated in Fig. 1, there was no detectable cytotoxicity at concentrations ranging from 0.78-6.25%. Therefore, the MSCE concentration range of 1.25-5% was used for the subsequent experiments.
Effects of MSCE on melanogenesis in B16F10 and MelanA cells. The effects of MSCE treatment on melanogenesis in mouse cells were examined. To determine whether MSCE inhibits melanin production in mouse cells, melanin content was measured following 3 days treatment with MSCE at concentrations of 1.25-5%. In cells treated with α-MSH, melanin levels in the media increased compared with untreated cells, due to an induction of melanogenesis ( Fig. 2A). However, cells co-treated MSCE exhibited a dose-dependent reduction in melanin pigmentation in B16F10 and Melan-A cells, compared with cells treated with α-MSH alone ( Fig. 2A). PTU, a well-known TYR inhibitor (4), was used as a positive control; PTU treatment inhibited melanin pigmentation compared with cells treated with α-MSH alone ( Fig. 2A).
Melanogenesis is regulated by an enzymatic cascade that is under the control of TYR (23). For this reason, various compounds that have been developed for skin-whitening purposes directly inhibit TYR (24). The effect of MSCE on TYR activity was examined using a mushroom TYR activity assay. Treatment with 50 µM kojic acid, a direct inhibitor of TYR that was used in this assay as a positive control, resulted in significant inhibition of TYR activity (Fig. 2B). However, treatment with various concentrations of MSCE did not inhibit mushroom TYR activity (Fig. 2B). These results demonstrated that the inhibitory effect of MSCE on melanogenesis was not mediated by the direct inhibition of TYR.

Effects of MSCE on melanogenesis signaling pathways in B16F10 and MelanA cells.
To investigate whether the inhibitory effect of MSCE is related to the melanogenesis signaling pathways, mouse cells were treated with α-MSH and/or MSCE, and the protein expression levels of TYR, TRP-1, TRP-2 and MITF was examined by western blotting. As demonstrated in Fig. 3A, the protein expression levels of TYR, TRP-1 and TRP-2 were reduced following co-treatment with MSCE for 24, 48 or 72 h, compared with the α-MSH-treated group in B16F10 cells. In addition, MITF protein expression levels were reduced in a time-dependent manner compared with the α-MSH-treated group in B16F10 cells (Fig. 3A). These results indicated that MSCE treatment inhibited melanin production  through the reduction of MITF and TYR expression levels. The inhibitory effect of MSCE on TYR expression in the mouse cell lines was confirmed by immunocytochemistry. The results indicated that TYR levels were reduced following MSCE treatment for 72 h, compared with the α-MSH-treated group in B16F10 cells and with the untreated group in Melan-A cells (Fig. 3B).

Effects of MSCE on signal transduction pathways in mouse cells.
In an attempt to identify the underlying mechanisms involved in the MSCE-mediated cell depigmentation, the effects of MSCE treatment (5%) on the activation of ERK, JNK and p38 MAPKs were examined by western blot analysis. In B16F10 cells treated with MSCE for up to 720 min, ERK and JNK phosphorylation was greatly increased at the 30 and 60 min time points, respectively (Fig. 4A). By contrast, p38 phosphorylation increased in expression slightly (Fig. 4A). In Melan-A cells, ERK phosphorylation was notably increased at 10 min following MSCE treatment, whereas p38 phosphorylation was slightly increased at 120 min. However, no change to JNK levels (Fig. 4B). To determine the possible involvement of p38 and JNK signaling on the MSCE-mediated inhibitory effect, cells were treated with the JNK and p38 inhibitors (SP600125 and SB203580, respectively) and melanin production was analyzed following MSCE treatment. The results revealed no effect of the inhibitors on melanin production following MSCE treatment (data not shown).

Effects of MSCE on melanogenesis and ERK phosphoryla tion.
The phosphorylation of ERK has been reported to inhibit TYR expression, which subsequently reduces cellular melanin production (25). Therefore, the present study examined whether the MSCE-induced activation of the ERK signaling pathway may be important for the MSCE-mediated inhibition of melanin production in B16F10 and Melan-A cells. For this purpose, mouse melanocyte cells were treated with MSCE for 30 min in the presence or absence of PD98059, a MEK inhibitor. As demonstrated in Fig. 5A, the melanin contents of B16F10 cells co-treated with α-MSH and PD98059 were higher compared with cells treated with α-MSH alone. Melan-A cells treated with PD98059 did not demonstrate any significant difference in melanin levels (data not shown). This synergistic effect of α-MSH and PD98059 on melanin content was reduced by MSCE treatment (Fig. 5A). The effects of PD98059 treatment on MSCE-induced ERK phosphorylation was examined by western blotting, which revealed a reduction of ERK phosphorylation levels in the MSCE-treated mouse cells following PD98059 addition (Fig. 5B). These results indicated that ERK phosphorylation may be involved in the MSCE-mediated reduction of melanogenesis.

Discussion
Pigmentary disorders, including melasma, lentigo, post-inflammatory hyperpigmentation and dark circles, are associated with abnormal regulations of melanin synthesis or melanosome transfer (26). These disorders irregularly darken the skin of patients, and may cause discomfort or nervousness in everyday life. Several depigmentation compounds have been created and have both medical and clinical applications in skin. However, many of these compounds produce toxic and unwanted side effects owing to the inclusion of potentially harmful ingredients, such as mercury and high levels of hydroquinone (27). For this reason, research has been focused on the development of safe and effective alternative whitening compounds. Various natural products originating from marine organisms and plants have been investigated for effects on pigmentation, including TYR, TRP-1 and TRP-2 expression, and are used as traditional whitening compounds (28). The present study demonstrated the inhibitory effects of MSCE on melanin synthesis in B16F10 and Melan-A cells and its underlying mechanism.
Yoon et al (29) previously reported an effect of sea cucumber on the expression of several melanogenic proteins, including TYR, TRP-1, TRP-2 and MITF. Furthering this research, the present study investigated the mechanism of MSCE as a novel skin-whitening compound. The results further established that MSCE functions via the inhibition of TYR, TRP-1, TRP-2 and MITF protein expression. The effects of MSCE were dose-dependent and did not produce any critical cytotoxicity at doses between 1.25 and 5% that were used for the melanogenesis assays. TYR has been reported to  catalyze the rate-limiting phase of melanin synthesis, and it is the first target of PTU, a compound with important depigmentation effects that was recently employed for medical and cosmetic purposes (30). MSCE treatment did not significantly alter TYR activity when tested on mushroom TYR; however, MSCE treatment did significantly decrease melanin synthesis in B16F10 and Melan-A cells in a dose-dependent manner. These results suggested that MSCE did not directly inhibit TYR activity, indicating that the effects may be a result of indirect mechanisms. Thus, the MSCE-induced depigmentation may be the result of inhibitory effects on the signaling pathways controlling TYR expression.
To understand the results of the present study, the mechanisms involved in MSCE-mediated melanogenesis inhibition were investigated. Western blot analysis of melanogenesis-related proteins was performed, and the results suggested that MSCE treatment reduced the protein expression levels of TYR, TRP-1, TRP-2 and MITF in a time-dependent manner. In addition, MSCE treatment reduced the melanin content compared with untreated cells. The effects of MSCE on TYR expression, which regulates melanin synthesis in B16F10 and Melan-A cells, were confirmed using immunocytochemical analysis. The results indicated that the TYR protein expression levels in B16F10 cells and Melan-A cells were reduced following treatment with MSCE for 72 h compared with untreated cells.
The MAPKs, including ERK, JNK and p38 MAPK, are important in regulating melanogenesis (31). To explain the mechanisms underlying the depigmentation effects of MSCE treatment, changes to the activation/phosphorylation of ERK, JNK and p38 MAPK were examined in a time-course MSCE treatment experiment using western blot analysis for 0-720 min. The results demonstrated that the phosphorylation of ERK was significantly increased and phosphorylation of JNK was slightly increased following MSCE treatment compared with untreated cells; however, p38 MAPK phosphorylation remained unchanged. These findings suggested that MSCE-induced depigmentation in B16F10 and Melan-A cells may occur through MAPK-regulated signaling pathways. To identify which MAPKs may be mediating MSCE-induced melanogenesis inhibition, B16F10 and Melan-A cells were analyzed in the presence of SB203580, a p38 inhibitor, and PD98059, a specific MEK inhibitor. Although SB203580 had no effect in melanin production (data not shown), PD98059 markedly increased MSCE-suppressed melanin contents in B16F10 cells. In addition, the PD98059-induced suppression of p-ERK expression was reversed by MSCE treatment in α-MSH-treated B16F10 and Melan-A cells. Notably, it has previously been reported that ERK is an important regulator of melanogenesis, as ERK phosphorylation induces MITF activation and its following degradation, and thus, inhibits melanin synthesis. In addition, the phosphorylation of ERK inhibits melanin synthesis through the suppression of TYR expression (32). The effects of MSCE on melanogenesis and phosphorylation of ERK demonstrated in the present study are in accordance with the known role of the ERK signaling pathway in melanin synthesis.
In conclusion, the present study demonstrated that MSCE treatment led to the phosphorylation of ERK and JNK, which suppressed the degradation of MITF, TYR, TRP-1, and TRP-2 in B16F10 and Melan-A cells, subsequently reducing melanin synthesis. Therefore, the results suggested that MSCE may be a useful depigmenting compound that may be used in the treatment of unwanted pigmentation conditions and may be a novel future therapeutic in the medical and cosmetic industries.


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Breast Cancer Cell Line Classification and Its Relevance with Breast Tumor Subtyping

Breast cancer cell lines have been widely used for breast cancer modelling which encompasses a panel of diseases with distinct phenotypical associations. Though cell lines provide unlimited homogenous materials for tumor studies and are relatively easy to culture, they are known to accumulate mutations duringthe initial establishment and subsequent series of cultivations. Thus, whether breast cancer cell line heterogeneity reflects that of carcinoma remains an important issue to resolve before drawing any reliable conclusion at the tumor level using cell lines. Inconsistent nomenclatures used for breast cancer cell line subtyping and the different number of subtypes grouped for cell lines and tumors make their direct matching elusive. By analyzing the molecular features of 92 breast cancer cell lines as documented by different literatures, we categorize 84 cell lines into 5 groups to be consistent with breast tumor classification. After combing through these cell lines, we summarized the molecular features, genetically and epigenetically, of each subtype, and manually documented 10 cell lines lacking explicit information on subtyping. Nine cell lines, either found inconsistent on their primary molecular features from different studies or being contaminated at the origin, are not suggested as the first choice for experimental use. We conclude that breast tumor cell lines, though having a high mutational frequency with many uncertainties and could not fully capture breast cancer heterogeneity, are feasible but crude models for tumors of the same subtype. New cell lines with enriched interferon regulated genes need to be established to enlarge the coverage of cell lines on tumor heterogeneity.

Introduction
Breast cancer is highly heterogeneous encompassing a group of genetically and epigenetically distinct diseases exhibiting diverse clinical features [1]. A large proportion of current knowledge on breast carcinomas are derived from in vivo and in vitro studies performed using breast cancer cell lines, given that they could provide an unlimited source of homogenous self-replicating materials using simple yet standard media and approaches [2]. Thus, whether these cell lines well capture the molecular features and reflect the heterogeneity of corresponding tumors remains an important issue to resolve before obtaining any clinically relevant results. Though it is concluded that breast cancer cell lines are representative of breast carcinoma to a large extent, with ER and HER2 being important stratifiers for their classification, continuous evidences have suggested dramatic genetic and epigenetic changes during the initial cell line establishment and subsequent serial passaging, suggesting that the resultant cell lines may have evolved significantly from the primary tumors [3]. Also, different studies Ivyspring International Publisher categorize breast cancer cell lines into different groups [1,[4][5][6][7][8], complicating our understandings towards cell line classification and their relevance with tumors. For example, Birnbaum et al. grouped 27 breast cancer cell lines into luminal, basal and mesenchymal subtypes [7]; Riaz et al. characterized 5 subtypes, i. e. , luminal, luminal-HER2+, ER-negative-HER2+, basal, normal-like, among 51 breast cancer cell lines using a panel of 496 genes identified by Perou [1]; Lehmann et al. subdivided triple negative cell lines into 7 categories, namely, basal-like 1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M), mesenchymal stem-like (MSL), luminal androgen receptor (LAR) and unstable (UNS) [9]; and some studies discriminate breast cancer cell lines into luminal-like and basal-like, with the basal class further subdivided into basal-A and basal-B [5,8]. Given the inconsistent nomenclatures, classification and even contradictory molecular characterization in different literatures [1,[4][5][6][7][8]10], we are overwhelmed with cell lines lacking systematic feature documentation and consistent subtyping. On the other hand, the number of cell lines widely used for breast cancer studies is extremely small, with cell lines such as MCF7, T47D and MDAMB231 accounting for more than two-thirds of cell lines used in the associated studies [2]. This raises the issue on how representative these few cell lines are of the vast diverse spectrum of breast tumors with distinct clinical implications. We are thus motivated to sort out the molecular features and corresponding tumor subtype each cell line represents to facilitate breast cancer modeling using appropriate cell lines.

Nomenclature of breast cancer cell lines
Ever since the establishment of the first breast cancer cell line, BT-20, in 1958 [11], relatively few cell lines have been obtained due to technical difficulties in extracting viable tumor cells from the surrounding stroma [12,13] and the bottleneck of long-term propagation during cultivation [12,14]. Most cell lines were established in late 1970s.
Cell line naming does not, in general, reflect its phenotypical association, but rather how they are established regarding, e. g. whether they are derived from the same laboratory, the same patient, isolated by serial subculture from the same initial population, or cultured using the same approach. For instance, 'HCC series' cell lines, as represented by their names, were isolated at Hamon Cancer Centre [12]; 'MDA series' were established from M. D. Anderson Hospital and Tumor Institute [14]; '21 series' were established from the same patient diagnosed as having infiltrating and intra-ductal mammary carcinoma, despite their distinct phenotypes and genotypes [15]. 'HMT series' underwent a successive subcultivation under various conditions during their establishment, including P53 mutation, MYC amplification, EGF-independence accompanied by tumorigenicity in nude mice, EGFR and HER2 over expression. 'SUM series', though isolated from different tumor specimens, were established using the same selective media [16]. As cell lines are typically named by the scientist who derived them, there is no rule on how each cell line is named especially for those do not belong to any series. It is until recently that standardization on cell line nomenclature has been proposed [17], which helps regularize the naming of newly established cell lines and ultimately improvement in cell line annotation and scientific reproducibility [18].

Molecular classification of breast cancer cell lines
Gene expression profiling has been widely applied to catalogue breast cancer cell lines, with diverse number of clusters being matched into various schemes. We characterized 84 cell lines based on the status of three important receptors conventionally used for breast cancer subtyping, i. e. , estrogen receptor (ER), progesterone receptor (PR), and human epithelial receptor 2 (HER2), and classified them using the same nomenclature, i. e. , luminal A, luminal B, HER2 positive, and triple negative subtypes, with triple negative cells being further divided into A and B to capture its heterogeneity and provide an easy link to the widely used names, i. e. , basal A and B (Table 1).

Luminal breast cancer cell lines
Luminal breast cancer cell lines are characterized by positive ER and/or PR expression, despite the existence of a few exceptional cases, such as IBEP-1 and IBEP-3 [22], where PR positivity drives their luminal phenotype. This type of cell lines exhibits high expression of a panel of luminal feature associated genes/proteins including, e.g., ESR1 (ERα or ER), luminal keratins (KRT8/18/19), and transcription factors such as GATA3 and FOXA1. A systematic study on miRNA expression profiling has unveiled distinctive over-expression of has-miR-501-5p, has-miR-202, has-miR-760 and has-miR-626 in luminal cell lines [1]. Luminal cell lines are comparably more differentiated and have less propensity for migration due to tight cell-cell junctions, consistent with that at the tumor level.
Though the majority of the studies do not further stratify luminal cell lines into luminal A and B subtypes according to their HER2 status, we embrace such a differentiation not only for the sake of achieving consistent categorization with tumor subtyping to facilitate easy tumor modelling but also satisfying the requirement of drug response assays hinging on ER and HER2 status. For example, a study using BT474 (ER+HER2+) has revealed the synergistic advantage of tamoxifen and Herceptin in the treatment of breast tumors [23], and MCF7 (ER-HER2) has been conventionally used for testing tamoxifen-induced cell response [24]. Luminal B cell lines are, in principle, more invasive and consequently more aggressive than luminal A cells, as HER2 over-expression is shown to be associated with ER down-regulation [2]. Thus, luminal B cells participate in the phenotype attenuation of luminal A cells, and could be more appropriately described as weakly luminal [2]. Lots of information for luminal B tumors has been successfully deciphered using cell lines of this subtype with translational potential at clinics [25][26][27][28]. For example, the expression of quiescin-sulfhydryl oxidase 1 is reported to be associated with a poor prognosis in luminal B tumors using a ER+HER2+ cell line, BT474 [29], suggesting the usefulness and importance of separating luminal B cell lines from the luminal subtype.
HER2 positive cell lines bridge the gap between luminal and basal cell lines, and are heterogeneous encompassing both luminal and basal features. They are grouped as luminal-ERBB2+ and ER-negative-ERBB2+ in [1] according to the expression of luminal and basal markers besides ER and HER2 expression. Consistent with their molecular features, cells of this subtype are more aggressive with respect to cell migration as compared with luminal cells, since HER2 over-expression is associated with the breakdown of cell-cell junctions [2]; and more responsive to certain drugs and is an excellent model for the examination of Herceptin response, as a significant correlation is revealed between the molecular signature and biological response by Pearson's correlation test [5]. Proteins whose expression are strongly correlated with such a drug response include increased levels of ESR1, MAPK1/3, MEK, TYK2, FASN, and GRB7, which are mostly associated with cell proliferation, and up-regulated expression of SFN, CAV2, GRB2, RB1 and FLNA indicates a drug resistance [5]. Thus, by studying cell lines over-represented by HER2 expression, MAPK signaling is shown to predict Herceptin response, and mTOR pathway, Toll-like receptor pathway, N-glycan biosynthesis as well as inositol-phosphate signaling are associated with Herceptin resistance [5]. translational level as a whole, which characterize triple negative A cells when combined with basal keratins (KRT5/6), CD10, and MET, and identify triple negative B cells when jointly assessed with the stemness marker CD44 [7]. Distinct microRNAs are detected for triple negative A and B cells. In particular, hsa-miR-492, has-miR-26b, has-miR-617, has-miT-155 are overtly expressed in the triple negative A subtype, and hsa-miR-22, hsa-532-3p, hsa-miR-125b, hsa-miR-501-5p, hsa-miR-155* pop up in the triple negative B subtype [23]. Interestingly, hsa-miR-155 (triple negative A) and hsa-miR-155* (triple negative B) are derived from the same precursor, but show an opposing expression pattern in these two triple negative subtypes [1]. Phenotypically, triple negative A cells, as a comparatively more differentiated subtype within triple negative cell lines, may have either luminal-like or basal-like morphologies, whereas triple negative B cells has a more mesenchymal-like appearance and are more likely invasive. Thereby, triple negative A lines mostly resemble the core basal tumor subtype as featured by basal markers, and triple negative B cells could be used for claudin-low or metaplastic breast cancer modelling given their enrichment in epithelial mesenchymal transition (EMT) and stem-cell markers [31].

Triple negative breast cancer cell lines
BRCA1 encodes a protein forming the Rap80/Abraxas/Brca1/Brcc36 complex in response to DNA damage [32]. Mutation of this gene predisposes hereditary breast cancer, which also resembles sporadic core basal tumors [33][34][35]. Triple negative A lines are characterized by BRCA1 signatures [8], with most of the currently available BRCA1 mutated commercial breast cancer cell lines (HCC1937, MDAMB436, SUM149PT, HCC3153) belonging to this subtype except for SUM1315MO2 (Table 1).
There are ten triple negative cell lines, DU4475, KPL-3C, MA11, HCC1739, CAL148, MFM223, CAL120, CAL51, CAL851, HDQ-P1, lacking direct information for further discrimination. We infer DU4475, KPL-3C, MA11, CAL148, MFM223 as triple negative A, and the rest as triple negative B based on the relevant literatures [5,6,12,20,36,37,[39][40][41]. DU4475 cells carry a mutation in the gene MAP2K4 whose alteration is characteristic of luminal features [6], agreeing with the fact that triple negative A cells may have either luminal-like or basal-like morphologies [5]. Immunohistochemical studies reveal the expression of keratins but not vimentin in KPL-3C [36], fulfilling our classification criteria of triple negative A cells (Table 2). MA11 is characterized by MUC1 secretion [37], whose expression occurs at a high frequency in early stage basal A triple negative breast cancer [20]. CAL148 and MFM223 are classified as the triple negative A cell line given their negative expression on vimentin [39]. CC1739 is a poorly differentiated cell line [12], satisfying the stemness feature of triple negative B cells. CAL120, CAL51 [40], CAL851 and HDQ-P1 [41] are positive on vimentin expression, falling into the triple negative B group. Our categorization of these cell lines is in agreement with other studies where different classification schemes were used. For example, Lehmann et al. categorized CAL148 and MFM223 to the LAR subtype which are heavily enriched with hormonally regulated pathways [9], suggesting their close relationship with hormone responsive cell lines and corroborating our classification of them as triple negative A than triple negative B cells.

Breast cancer cell lines are feasible models of breast cancer
The occurrence of DNA alterations was higher in breast cancer cell lines than in tumors. On average, alterations in cell lines are about two-fold more frequent than those in tumors [2,21]. This might be because that breast cancer cell lines are mostly originated from invasive high-grade tumors, which are more easily to accumulate genomic aberrations during in vitro cultivation. Breast cancer cell lines may exhibit DNA alterations not detected in tumors, which may result from the sequential cultivation or reflect low frequency alteration in tumors that is hard to observe. Such newly gained mutations may cause phenotypical changes to cells. For example, MCF7 cell lines with variable sensitivities to tamoxifen are reported [42]. However, CGH analyses suggest that breast cancer cell lines are representative of tumors with regard to major DNA alterations [21]. A comprehensive study comparing the HCC series of cell lines with their original tumors reveals that almost all aberrations (except one) presented in a tumor also occur in the corresponding cell line [43]. This has been confirmed by another study comparing allelic losses at 18 chromosomal regions frequently deleted in breast tumors using 51 polymorphic micro-satellite markers [20]. Also, it seems that DNA alterations affecting specific genes under our interest remain highly consistent between cell lines and tissues. For example, a 75% concordance was seen on the mutation status in exons 5 to 10 of TP53 gene [44]. Point mutations identified in tumors were often found in at least one or some cell lines and vice versa [2]. At the chromosomal level, breast cancer cell lines, though, have a higher copy number changes, share a similar pattern regarding gains and losses with tumors [2,21].
Epigenetic alterations are heritable modifications of gene expression that do not involve mutation, which are similar between breast cancer cell lines and tumors. A study has revealed that the CpG island methylation pattern is very close between cell lines and tumors. In their study, most of the genes harboring CpG island hypermethylation in the promoter region are present in both breast cancer cell lines and tumors such as ER, PR, HIC1, APC, ARHI, ASC, BRCA1, CCND2, CDH1, CDH13, CDKN2A, FABP3, FHIT, GIB2, GPC3, GSTP1, HOXA5, HSHIN1, KLK10, NME1, PRDM2, PRKCDBP, RARB, RASSF1, SFN, SYK, TFF1, TIMP3 and WT1 [45]; and quite a few cases show inconsistency between cell lines and tumors, e. g. , IL6, GSN, PLAU, PRSS8, SLC19A1, SNCG are hypermethylated in tumors but not in cell lines and the hypermethylation of PLAGL1, TGFB3 is observed in cell lines but not tumors [45].
At the molecular level, discriminative markers and associated phenotypic traits observed in breast cancer cell lines are also frequently discriminative features in tumors. Genes correlated to the ER+ or ERphenotype in breast cancer cell lines are positively or negatively correlated to ER expression in tumors. The mRNA variants of ER containing precise truncations in various exons have been identified in both cell lines and tumors [46].

Breast cancer cell lines are crude models of breast cancer
Despite the considerable roles played by breast cancer cell lines in deciphering the mechanisms underlying tumor initiation and evolution, cell lines are still viewed as crude models of tumors and could not capture all tumor features and heterogeneity.
The clonal population comprising of any single cell line could not well capture the heterogeneity of breast tumors at the intra-tumoral level. Carcinogenesis is a sequential process through many clinical and pathological stages including a typical hyperproliferation, local invasion, invasive carcinomas and ultimately metastatic disease, and is believed to be accompanied with a sequential acquisition of various genetic and epigenetic alterations in a single cell followed by clonal selection and expansion. The establishment of cell lines, on the other hand, may eliminate some types of tumor cells initially present in the tissue samples under the environmental stress created by the cultivation condition. For instance, cells unable to grow properly on plastic or need specific factors secreted by tumor microenvironment may be eliminated during the cultivation process. Thereby, how well a permanent breast cancer cell line could model the tumor intra-heterogeneity becomes a questionable issue.
Success in long-term propagation has been a limiting factor during the establishment of breast cancer cell lines, resulting in less commercially available cell lines than needed to cover the inter-tumoral cancer heterogeneity. Take triple negative breast cancer as an example, it encompasses at least four subtypes, i.e., core basal, claudin-low, metaplastic breast cancer, and interferon-rich, each with distinct molecular features and clinical associations. However, we only have triple negative A and B cell lines. While type A may be well representative of the core basal tumor subtype, and type B is useful for the modelling of claudin-low and/or metaplastic subtype (further differentiation among type B lines is needed), we are left with no suitable cell line for interferon-rich tumor modelling according to their molecular features. Also and importantly, very few breast cancer cell lines (e. g. , MCF7, T-47D, MDAMB231), despite the total number of established ones, have been frequently used for research purpose for the sake of, e. g. , cultivation easiness, rendering the transportability of results obtained from such limited number of cell lines to the evolving tumors even more questionable.
Given the technical difficulties of extracting viable tumor cells from their surrounding stroma, most breast cancer cell lines are originated from invasive carcinoma (Table 1), raising the questions as to how they are representative of the primary tumors. Also, we could not exclude the possibility that certain breast cancer cell line, either from origin or due to cultivative selection, are not representative of breast cancer cell at all. For example, MDAMB435, previously identified as a breast cancer cell line, has been suggested as being originated from an occult melanoma [47].
Also important is how much tumor microenvironment affects cell signaling, and how much these changes alter cell molecular features and affect the experimental results. A study examining the influences of fibroblasts on cell line morphological changes using EMG3 reveals that fibroblasts could stimulate the expression of luminal keratins in basal cells and/or basal keratins in luminal cells [48]. Also reported is that cells developed in an environment with high/low EGFR activity tend to become ER negative/positive [49], suggestive of the selective power imposed by microenvironment on cells. This makes experiments convolving tumor microenvironment difficult to be modeled using cell lines.
This renders not only studies hinging on cell lines difficult to be compared with but also our understandings towards these cell lines complicated and confusing at the first hand.

Discussion
By summarizing and comparing the molecular features of breast cancer cell lines currently available to our knowledge with tumors, genetically and epigenetically, we categorize them into five subtypes, i. e. , luminal A, luminal B, HER2 positive, triple negative A and triple negative B. Unlike at the tissue level where luminal tumors dominate (63% [50]), cell lines of this subtype take the least percentage (31%) among all, i. e. , 17 are luminal A, 9 are luminal B, 20 HER2 positive, 21 triple negative A, and 17 triple negative B among the lines under study. This is due to the fact that most lines are derived from invasive carcinoma for the sake of easy cultivation, toppling the uneven distribution encountered at the tumor level.
In our nomenclature, luminal A and B cell lines are differentiated from each other and HER2 positive lines are identified as a single subtype to facilitate studies on tissue subtyping and drug response experiments targeting ER and/or HER2 using cell lines. Triple negative lines are identified as two separate groups, which correspond to basal A and B as referred to in most literatures. While triple negative lines share a panel of feature markers such as EGFR which has been used as a conventional marker characterizing triple negative tumors in many studies [51][52][53][54][55][56], each has its own distinct molecular and phenotypical properties. Triple negative A is characterized by the expression of basal keratins (KRT4/5/6/13/14/15/16/17) which resembles the core basal tumors, and triple negative B is featured by the cancer stem cell pattern such as CD44+CD24-and migration markers such as VIM which could be used for modeling of claudin-low and/or metaplastic breast cancers. Among the collected 92 cell lines here, 74 are unanimously labeled with one subtype as suggested by existing literatures, 10 (DU4475, KPL-3C, MA11, HCC1739, MFM223, CAL148, CAL120, CAL51, CAL851, HDQ-P1) are categorized by their available information based on our subtyping criteria (Table 1), 8 (Table 3) have ambiguous and inconsistent categorization among different studies which may have evolved into different cell lines in different labs after serial cultivation, and one (MDAMB435) is found not of breast cancer origin.
Breast cancer cell lines, though having a higher frequency of DNA and/or copy number alterations, share a similar major genetic mutational spectrum and chromosome aberration profiles with tumors, allowing them still feasible for tumor modelling. However, cell lines are crude models for cancer research as they could not well capture the intra-and inter-tumor heterogeneities, and how well they could represent primary tumors and how much they evolve from their initial establishment are still questionable especially for a few cell lines whose characterization on the primary markers are inconsistent across studies. Thereby, it is encouraged to use breast cancer cell lines for initial tumor modelling but the results need to be further validated using tumor samples or mouse models. Also, cell line selection becomes critical, which needs to be representative and the relevant and/or determinant markers need to be pre-tested.
Cultivation medium is crucial for the success of cell line establishment, regarding how well cells maintain their molecular and physiological features in tumor tissue. Currently widely applied medium include RPMI, DMEM, /αMEM , Ham's F12, L15, McCoys etc. , with RPMI, DMEM, αMEM, Ham's F12 providing a full coverage of all the cell lines in Table 1. The amino acid concentration of these medium, ranging from the most enriched to the least are αMEM, DMEM, RPMI and Ham's F12. The observation that DMEM is rather frequently used for the cultivation of luminal cells, Ham's F12 is many times used in triple negative cells and occasionally in HER2 positive cells suggest that the more aggressive and invasive tumor cell lines are the fewer nutrition is needed in the medium.

Concluding Remarks
By summarizing and going through all the molecular features of currently available cell lines, we grouped them using a subtyping system compatible with that in tumors, and clarified some ambiguous information regarding cell molecular and morphological features. This helps us in the proper choice of and widens the selection spectrum of cell lines when conducting relevant studies, which is critical in the guarantee of final successof translating cell line based results to clinics.
Systematic analysis on the molecular differences between cell lines and tumors reveal that breast cell lines, on average, harbour more genetic mutations and approximately the same amount of epigenetic aberrations than the tumors they derive. The key molecular features of cell lines, however, remain the same with tissue tumors, except for a few exceptional cases whose primary markers have evolved into multiple versions. Also, despite the more frequent chromosomal alterations occurred in cell lines, their genomic profiles stay invariant with the tumors. These empower breast cancer cell lines feasible models for tumors of the same subtype. However, they are not accurate models to capture the full heterogeneity of tumors, both at a single line level or the whole cell population. Also, how much they are evolved from the corresponding primary tumors, either due to technical ease at the establishment or during serial cultivation, remain to be elucidated. In addition, without interactions with the microenvironment, whether or not cell lines could reproduce the signaling in situ worth serious considerations before cell lines are chosen for the experiments.
It is worth noting that, our claim that 'cell lines are feasible models for tumors' refers to tumors of the same subtype but not the tumor deriving the cell line. Some cell lines, after passage selection under, e. g. environmental stress, may alter their transcriptional profiles and exhibit the features of another subtype. For instance, EMG3, a triple negative A cell line showing KRT5/14 positivity in the immunocytochemical analysis, is originated from tumors characteristic of luminal markers such as KRT18/19 [57]. Triple negative breast cancer, though, do not dominate the patient cases, are very heterogeneous, encompassing at least four subcategories. However, we only have two subgroups within cell lines of this category, leaving no cell line being appropriate for interferon-rich tumor modelling. As a subtype with approximately 10% prevalence among tumors [31], it is suggested to establish triple negative cell lines modeling such tumors which represent a 3rd triple negative subtype and enrich the heterogeneity of current cell line modality.