ERG that promotes stem cell characteristics. The AML-enriched H3K9me2 blocks (in contrast to the heterochromatin-associated H3K9me2 blocks enriched in granulocytes) are reduced by pharmacological inhibition of the histone methyltransferase G9a/GLP in K562 cells concomitantly with transcriptional activation of ERG and ETS1 oncogenes. Our data suggest that G9a/GLP mediate formation of transient H3K9me2 blocks that are preserved in AML myeloblasts and may lead to an increased rate of AML-specific mutagenesis and chromosomal translocations.A facultative heterochromatin mark, histone H3 lysine 9 dimethylation (H3K9me2), which is mediated by histone methyltransferases G9a/GLP (EHMT2/1), undergoes dramatic rearrangements during myeloid cell differentiation as observed by chromatin imaging. To determine whether these structural transitions also involve genomic repositioning of H3K9me2, we used ChIP-sequencing to map genome-wide topography of H3K9me2 in normal human granulocytes, normal CD34+ hematopoietic progenitors, primary myeloblasts from acute myeloid leukemia (AML) patients, and a model leukemia cell line K562. We observe that H3K9me2 naturally repositions from the previously designated “repressed” chromatin state in hematopoietic progenitors to predominant association with heterochromatin regions in granulocytes. In contrast, AML cells accumulate H3K9me2 on previously undefined large (> 100 Kb) genomic blocks that are enriched with AML-specific single nucleotide variants, sites of chromosomal translocations, and genes downregulated in AML. Specifically, the AML-specific H3K9me2 blocks are enriched with genes regulated by the proto-oncogene  In eukaryotic chromatin, the DNA is repeatedly coiled around octamers of small basic proteins, histones, to form nucleosomes . ChromatLarge Organized Chromatin K9 domains (LOCKs) that are notably altered in cancer cells [While DNA methylation and Polycomb repressive complexes are among the most studied epigenetic factors related to human leukemia , 12, in er cells , 18. Viser cells –21. The er cells .Most of H3K9me2 modification in mammalian cells is mediated by the euchromatin histone methyltransferase (HMTase) G9a/GLP (EHMT2/EHMT1), which is essential for mouse embryonic development and embryonic stem cell differentiation , lineageG9a/GLP and histone H3K9me2 methylation are involved in repression of multiple genes associated with AML –26 but tHere we asked whether the genome-wide positioning of H3K9me2 is altered in the human AML cells as opposed to the normal process of H3K9me2 spreading during myeloid differentiation, do these changes include any specific genomic regions showing gains or loss of H3K9me2 in all or certain types of AML, are these changes associated with coordinated transitions in gene expression and/or genomic instability, and whether these changes, especially those specific for AML, could be reversed by pharmacological targeting of G9a/GLP.Fig A in S1 File) and applied it to human myeloid cells including mature granulocytes, CD34+ progenitor cells, cultured K562 myeloid cells, and 10 samples of primary cells from the peripheral blood of AML patients. We identified AML-specific blocks of H3K9me2  coordinated with large-scale transcriptional changes in AML. We also observed wide-scale reduction in H3K9me2 levels associated with transcriptional changes following pharmacological inhibition of G9a/GLP in the leukemia model cell line K562. Strikingly, the new AML-specific H3K9me2 blocks contained a number of down-regulated proto-oncogenes, in particular genes transcriptionally regulated by ERG, a factor promoting adult hematopoietic stem cell self-renewal and expansion [To answer these questions, we developed a new approach to genome-wide analysis of large H3K9me2 blocks  and sites of chromosomal translocations known to cause AML. Provided that myeloid differentiation is essential for initiation of AML , we propS1 Table. Cryopreserved bone marrow CD34+ cells from normal donors were obtained from Allcells . Bone marrow CD34+ cells represent a combination of stem and progenitor cells and can be easily isolated at high cell numbers without cytokine mobilization [Fig A in Normal polymorphonuclear granulocytes (predominantly neutrophils) were isolated from discarded fresh white blood cells (buffy coats) from unidentified healthy donors collected at Hershey Medical Center Blood Bank (IRB protocol # HY03-136EP-A) using standard OptiPrep density centrifugation  and resu2 at 37°C. K562 cells were grown for not more than 10 passages after acquiring from ATCC. K562 cells were treated with 0–1 μM UNC0638 , with 0.01% (vol/vol) DMSO, for 5 days; medium was replaced on day 3 with fresh growth medium containing UNC0638 or DMSO vehicle only. Cells were incubated with UNC0638 at the concentration indicated, when not specified the K562 cells were treated with 1 μM UNC0638. Three biological replicates were performed, using independently cultured K562 cells. After treatment, K562 cells were washed 2 x PBS and then resuspended in PBS for fixation.Human K562 cells (ATCC CCL-243) were grown in RPMI 1640 GlutaMAX medium (Invitrogen) supplemented with 10% FBS  and 1% penicillin-streptomycin (Invitrogen), in 5% COFor chromatin immunoprecipitation (ChIP) and western blotting analyses, we have used anti-H3K9me2 ab1220), anti-H3K9me3 (ab8898), anti-H3 C-tail (ab8898) from Abcam; and Anti-H3K4me2 (07–030) from Upstate/Millipore. We have successfully tested these antibodies for immunofluorescence analysis, western blotting, and ChIP in previous works with myeloid  and othe, anti-H3SDS-PAGE was carried out in 15% polyacrylamide and the proteins were transferred to Immobilon-P PVDF membranes (Millipore) in Tris-glycine buffer containing 10% methanol. Membranes were blocked in 3% nonfat dry milk in TBS buffer with 0.1% Tween 20, and incubated with primary anti-H3K9me2 (ab1220), anti-H3K9me3 (ab8898), and anti-H3 C-tail (ab8898) from Abcam as previously described . Semi-qu7 cell/ml at room temp., mixed with 1/10 of the final volume of 10% formaldehyde in PBS freshly prepared from 37% stock . Cells were fixed with 1% formaldehyde for 10–15 min at room temp. Fixation was stopped by adding of 125 mM glycine. Cells were spun down at +4°C and 4000 g for 5 min. and washed 3 times cold PBS. The fixed cells were counted to estimate the yield and stored overnight at +4°C.For formaldehyde fixation, cultured cells or freshly thawed cells were suspended in PBS at ~ 5x102) at ~1 mg/ml DNA. The nuclear suspensions (1 ml) were digested with 60 units of Micrococcal nuclease (Roche) for 40 min. at + 37°C to ~200 bp nucleosome sizes and digestion was stopped by adding 3 mM EDTA. After digestion, the supernatant (S1) was collected and discarded and the nuclear pellet (P) was resuspended in SDS-containing Lysis buffer  with light sonication  to enhance solubility rather than to shear DNA. Chromatin immunoprecipitation (ChIP) was conducted essentially as described [Nuclei from formaldehyde-fixed cells were isolated as described . The purescribed . The finFor each sample, we conducted two parallel immunoprecipitation reactions with a) no antibody added; b) similarly prepared IgG from a none-immunized animal . A typical yield from immunoprecipitation with antibodies against H3K9me2  was more than 400 ng for 40 μg of the input (ChIP/Input ratio >1%). Nonspecific binding in the control samples was < 0.02%.6 70 bp DNA sequence reads per sample) using the SOLiD sequencer at the Penn State Genomic Core Facility (University Park). For next-generation Illumina sequencing library preparations, we used NEBNext ChIP-Seq single-end library preparation reagent set for Illumina (cat #E6200) and NEBNext Multiplex Oligos for Illumina Index Primers Set 1 (cat #E7335). For one library, we took 10–30 ng of chromatin-immunoprecipitated or input DNA. End repair of ChIP DNA, dA-Tailing, Adaptor ligation, and cleaning of DNA by AMPure XP magnetic beads (Agencourt part # A63880), were conducted according to the NEBNext ChIP-Seq library preparation manual with exception that after adaptor ligation and AMPure cleaning (step 4), the material was eluted in 20 μl of 0.1 x TE buffer for agarose gel size selection. DNA electrophoresis was run in 2% agarose gels with SyBr Gold gel stain  using TAE buffer and 100 bp DNA ladder (NEB N3231S) as size standard. We excised a band from the gel ranging in size from 175–225 bp (150 bp nucleosome plus 50 bp adaptors) using the DNA ladder as a guide. We purified the DNA using Qiagen QIAquick gel extraction kit (cat# 28704) and eluted in 50 μl of sterile water. We took 23 μl of eluted size-selected DNA for PCR enrichment using the universal primer and one of 12 index primers (from NEB cat #E7335) as described in the NEB Next ChIP-Seq library preparation manual. We used 15–17 cycles of PCR amplification depending on the amount of starting material. After PCR, we cleaned the PCR-amplified library DNA by AMPure XP magnetic beads, redissolved in 20 μl of 0.1 x TE buffer and measured the DNA concentration using Qubit fluorometer (dsDNA HS assay). Typical yield was 40–100 ng/μl. For quality controls, we assessed the DNA size distribution on a Bioanalyzer® . The DNA libraries were sent for deep sequencing using the Illumina Hi-Seq 2500 sequencer at Penn State Genomic Core Facility (University Park). We used rapid-run mode with 2 lanes, 4 samples per lane and 100 nucleotides per read. For each sample Illumina sequencing provided 32–40 million of 100 bp reads (see S2 Table for SOLiD and Illumina-sequenced samples).For SOLiD sequencing, the DNA samples  were submitted for preparing fragment libraries and their amplifications using Applied Biosystems reagents and deep sequencing . The RSEG domains calculated with predicted 10 kb values were used in this study. Other parameter used was: “keep duplicates”. The chromosome X and Y mappings were duplicated for the male samples prior to calling RSEG. Sequence reads mapped to multiple genomic locations were excluded from subsequent analysis. The RSEG enriched domains were mapped into windows of sizes 10 kb, 50 kb, 100 kb, 500 kb and 1Mb, with each domain contributing to a window’s score its average read count for each of its nucleotides falling within the window. Window scores for each dataset were then normalized by the average score of all its windows and technical replicates were then averaged. Supplementary files showing enriched RSEG domains and their boundaries are included in the GEO database (acc.# GSE71809) and contain “rsegout.bed.gz” in their filename extensions.Sequence reads were mapped to the hg19 assembly of the human genome using bowtie 0.12.9 with default parameters (see GEO database acc.# GSE71809 for the raw and processed sequence reads files associated with this study). Domains were called with the RSEG software, version 0.4.8 RC, using the provided deadzone files k41-hg19 . The sizCluster analysis of H3K9me2 sequence read distributions genome-wide and on specific chromosomal loci was done with open source Gene Cluster 3.0 software  with hiehttp://genome.ucsc.edu) table tool: 1–16: chromatin state segmentation by HMM from ENCODE/Broad Institute [S3 Table) was derived from the list of all AML-specific chromosomal translocations and inversions in the Atlas of Genetics and Cytogenetics in Oncology and Haematology (http://atlasgeneticsoncology.org/index.html). For correlation analysis, the RSEG k41-hg19 deadzones [S4 Table). Pairwise Pearson correlations were calculated using R 2.15.1.The following human ENCODE  datasetsnstitute ; 17, 18:nstitute ; 19–24: nstitute ; 25: NKInstitute ; 26–28: nstitute ; 30, 31:nstitute , 32–39: nstitute ; 40–42: nstitute ; 43: CpGnstitute ; 44: visnstitute . Additionstitute , 46: cannstitute ; 47: AMLnstitute ; 48: Lonnstitute . We alsoConserved high (“Red”) and conserved low (“Green”) H3K9me2 domains were determined by calculating the standard deviation of the 10 kb window scores of the H3K9me2 granulocyte, CD34+, and AML samples. Only the male samples were used to determine the conserved domains over the Y chromosome. A threshold of 1 standard deviation was used to classify a sample’s window as ‘high’ (score > stdev) or ‘low’ (score ≤ stdev). An overall window was classified as conserved low (“Green”) H3K9me2 domains when only 2 or less samples were ‘high’ and at most one was ‘high’ from each of the granulocyte, AML, and CD34+ categories. Analogously, a window was classified as conserved high (“Red”) when only 2 or less samples were ‘low’ with at most one ‘low’ from each category. All remaining windows were classified as variable H3K9me2 domains (“Yellow”).To set bases for dLOCK calculations, the 10 kb window RSEG entries were grouped into the following categories: a) granulocytes, b) CD34+ c) K562 control, d) K562-UNC0638 treated, e) AML cluster A, f) AML cluster B. For each group we counted a continuous stretch of 10 kb windows as a LOCK base if at least 50% of 10 kb windows in each row contained positive values. For each of the continuous LOCK bases, for category “c1” above (where c1 is one of a-f), a dLOCK c2>c1 10 kb window score was computed as the sum of the negative log ratio (Sum Log Ratio) of the 10 kb window score of a sample in the first listed category to that of a sample in the second for every possible first and second category sample pair. This result was then normalized by the number of pairwise terms in the sum. The X and Y chromosome dLOCK 10 kb sums only included terms of sample pairs having the same gender.S5 Table). For 10 categories of dLOCKs as well as for the 3 genomic zones as well as for each of the Red, Green, and Yellow genomic fractions, we calculated the enrichments of the genomic features from UCSC/ENCODE databases (S6 Table).Contiguous blocks of 10 kb windows were determined to be a positive dLOCK of size spanning those windows if the total score, defined to be the sum of the corresponding dLOCK 10 kb window scores, was positive, and a negative dLOCK for a negative total score. The threshold of significant positive dLOCKs was set to the 90 percentile, and that of significant negative dLOCKs to the 10 percentile. The latter calculation was performed using the ‘quantile’ function in R, with alpha = 0.90 and 0.10 respectively excluding Y chromosome LOCKs. We thus calculated ten categories of differential LOCKs (dLOCKs): 1. CD34+ > granulocytes; 2. granulocytes > CD34+; 3. CD34+ > AML cluster A; 4. AML cluster A > CD34+; 5. granulocytes > AML cluster A; 6. AML cluster A > granulocytes; 7. CD34+ > AML cluster B; 8. AML cluster B > CD34+; 9. K562 UNC0638 > K562 control; 10. K562 control > K562 UNC0638; each category including ALL dLOCKs, and dLOCKs with alpha <0.10, >0.90, <0.05, >0.05, <0.01, >0.99 (Table A in S7 Table). Ingenuity® Pathways (IPA build version 212183) was used to identify upstream regulators and significantly enriched canonical pathways, networks, diseases and disorders, molecular and cellular functions, physiological system development and functions, and toxicity lists. Ingenuity Pathway was used with the following parameters: reference set to Ingenuity Knowledge Base Genes Only, relationships to include set to direct and indirect, includes endogenous chemicals, and filter set to only consider molecules or relationships for the human species and where the confidence is set to experimentally observed.For each dLOCK set described above, the genes of the top 1%, 5% and 10% scoring dLOCKs  were extracted (see Table D in S7 Table).Total RNA was isolated from cryopreserved AML cells and human bone marrow CD34+ cells from normal donors  using Trizol® reagent  with 1 ml of Trizol reagent per 5–10 x 106 cells as described in the vendor’s manual. Isolated RNA was quantified using the Bioanalyzer RNA 6000 Nano Assay kit . Four AML type A and two AML type B samples randomly chosen from initial 10 AML samples and 6 normal donor samples were taken for this analysis. First strand cDNA was produced from 1.0 μg of total RNA using the standard protocol from the High Capacity cDNA Reverse Transcriptase kit . cDNA concentrations were quantified by absorbance using a NanoDrop ND-1000 Spectrophotometer . cDNA expression rates in AML were assayed using Illumina HumanHT-12 array containing hybridization probes with 33,732 distinct chromosomal positions and using normal bone marrow CD34+ cells as controls  was performed using FastStart Universal SYBR Green Master (Roche) on a Roche LightCycler 480 Instrument following the manufacturer’s instructions.S8 Table.For ChIP-qPCR assays, reactions were performed in triplicate, with two technical replicates for each sample. The fold enrichment of ChIP over input was calculated as 2 to the power of the quantification cycle (Cq) difference between input chromatin and ChIP samples. Genomic qPCR primers are listed in S8 Table. The (Δ(ΔCq)) method was used to calculate target mRNA levels relative to two housekeeping genes, GAPDH and TBP, with similar results; data relative to GAPDH is shown. Fold change in gene expression was calculated by comparing DMSO control- and UNC0638-treated K562 cells. Student’s T-Test was used to evaluate the statistical significance of RT-qPCR gene expression analysis in two independent biological replicates.For RT-qPCR, total RNA was extracted using Trizol (Invitrogen) and Direct-zol RNA MiniPrep kit (Zymo Research), and cDNA was synthesized using SuperScript II First-Strand Synthesis System and oligo(dT) (Invitrogen). Reactions for each target were performed in triplicate, with two technical replicates for each sample. Melt curve analysis was performed at the end of PCR to confirm the presence of a single, specific product. RT-qPCR primers are listed in Fig A in S1 File). K562 is a blastic myeloid leukemia cell line that has been extensively characterized as a tier I model cell of the human ENCODE project [To determine genome-wide rearrangements of H3K9me2, we conducted ChIP with anti-H3K9me2 and several control antibodies with normal human granulocytes, normal bone marrow CD34+ hematopoietic progenitors, and K562 human myeloid leukemia cell line  to ensure that the results of data analysis are independent of the next generation sequencing techniques. The sequence reads (omitting duplicated sequences) were aligned to the human genome hg19 (see GEO database acc.# GSE71809 for the sequence reads files associated with this study). At the chromosomal scale, the H3K9me2 ChIP reads were distributed evenly, with exception of the haploid X and Y chromosomes in males .Most ChIP-sequencing and mapping experiments were independently repeated on two sequencing platforms (SOLiD and Illumina) each resulting in about 20–30 mln. reads per sample  shows an example of typical genome-wide distribution of H3K9me2 with low levels of this mark associated with a region of high gene density and an extended block of high level of H3K9me2 associated with a gene desert (underlined by a red line). Similar Large Organized Chromatin H3K9me2 domains (LOCKs) were described previously for human placenta cells [ and ChIP-seq for total histone H3 using antibodies against its unmodified C-tail , as well as ChIP-seq showing sharp peaks of an active chromatin mark H3K4me2 . The input DNA and the H3 C-tail levels appear to be somewhat lower at the regions with high H3K9me2 consistent with the recent observation that micrococcal nuclease accessibility and release of mononucleosomes negatively correlates with two other epigenetic markers of repressed chromatin, H3K27me3 and H3K9me3 [Fig 2B below). Furthermore, the ChIP-seq data normalized to input DNA and histone H3 C-tail also show the same constitutive LOCK in both cell types  thus attesting for unique and specific genome-wide distribution of the histone H3K9me2 mark in myeloid cells.At the higher resolution, the H3K9me2 ChIP-seq reveals profound variations in the distribution of H3K9me2. A map of a chromosome 5 region in granulocytes at 10 kb resolution  and apparently similar to LOCKs described in human placenta [TERT gene repressed during granulocyte differentiation and reactivated in many types of cancer cells [S1 File; vertical red arrows). Therefore, we decided to characterize the extent and levels of H3K9me2 domains in the normal and myeloid leukemia cells in relation to other genome-wide biological data available from databases.The positions of the large H3K9me2 blocks were generally conserved over the chromosomes of granulocytes, CD34+ progenitors, and K562 cells .To determine the genomic positions and boundaries of H3K9me2 domains and eliminate possible artifacts and repeats known as “deadzones” we used RSEG, an unbiased procedure for selecting domain boundaries based on hidden Markov model (HMM) analysis of genome-wide ChIP-seq read distribution . First, S4 Table). Independent analysis of our experimental datasets showed a negative correlation of H3K9me2 with H3K4me2 in the three cell types  consistent with the boundary analysis. Interestingly, the two types of normal myeloid cells, granulocytes and CD34+ progenitors, both showed a higher positive correlation between themselves than with a leukemia cell line K562  prompting us a more extensive analysis of H3K9me2 in human AML cell (below).For genome-wide correlation analysis of H3K9me2 in K562, granulocytes, and CD34+ cells and comparison with our experimental datasets and available data from human genome databases (see refs. 41–55), the RSEG domains were grouped by 10 kb, 50 kb, 100 kb, 500 kb, and 1Mb windows and Pearson correlations were calculated for all experimental and database entries  thus confirming a tight association of H3K9me2 with chromatin states previously described as “repressed chromatin” and “heterochromatin” [Correlation analysis with multiple genomic datasets revealed several general features consistent with the expected function of H3K9me2 in establishing repressive and/or heterochromatic chromatin states: 1) strong positive correlation of H3K9me2 in K562, granulocytes and CD34+ cells with H3K9me2 distribution in human lymphoid T-cells  thus shoromatin”  in myeloS4 Table). Remarkably, we observed a striking contrast between the strong positive correlation of H3K9me2 with the previously defined “repressed” chromatin state [Fig 2). In addition, correlations with the insulator elements known to separate functional chromosomal domains [S4 Table).As expected from previous studies in non-myeloid cells , 53, 60,in state  and H3K2 domains  were notWe thus concluded that the H3K9me2 domains form a set of conserved large organized chromosomal blocks (LOCKs) whose association with gene deserts, low nuclease accessibility, and regions of increased occurrence of cancer-related SNV (reflecting their relative inaccessibility to DNA repair ), is uniS1 Table). For all AML H3K9me2 domains, we observed strongly positive (r > 0.5) genome-wide correlations between the individual AML cases as well as with the “normal” human samples–granulocytes and CD34+ progenitors . Seven AML samples  displayed a positive H3K9me2 correlation with repressed chromatin and insulators thus closely resembling CD34+ progenitors. In contrast, the other 3 AML samples  had negative or very weak correlation with insulators and repressed chromatin, more similar to granulocytes than to CD34+ and the other AML samples.Comparison of H3K9me2 domains in AML with multiple genomic biodata showed a wide variation in H3K9me2 correlations with two principle chromatin states : insulat. One cluster designated here as AML cluster A  contained all 3 CD34-positive cases of AML with features of less differentiated cells. The other cluster, designated AML cluster B (strong correlation with heterochromatin) showed features of more differentiated AML M4 and M5 and was characterized by high monocytic cell counts  contains dozens of genes encoding zinc finger (ZNF) proteins. An unsupervised cluster analysis of the chromosome 19 (50–59 Mb) locus  showed the same two distinct clusters as above , with AML cluster A showing strongly reduced H3K9me2 and AML cluster B showing distributions much closer to that of K562 cells and granulocytes. A 10 kb map of H3K9me2 HMM domains confirmed the differences between dLOCKs of the AML cluster A and cluster B  and also showed that the differences revealed by ChIP reflected actual histone H3K9me2 level variations and not the genomic copy number variations since the input DNA maps of normal and AML cells were almost identical . Furthermore, parallel ChIP-qPCR experiments with gene regions from selected chromatin regions in granulocyte and four AML type A and two AML type B samples randomly chosen from initial 10 AML samples were consistent with the results of ChIP-seq analysis  though qPCR data exhibited stronger individual variations than ChIP-seq. Therefore, in subsequent work, we focused our analysis of ChIP-seq data derived from AML cluster A, which is better represented in the current dataset.In addition to the changes in genome-wide correlations, mapping of H3K9me2 revealed prominent changes in large blocks of H3K9me2 often containing multiple genes. A striking example of such blocks on chromosome 19 showing the strongest H3K9me2 changes between normal and AML cells  is shown in The observation of large variable H3K9me2 blocks prompted us to conduct genome-wide comparative analysis of large blocks of H3K9me2. Therefore, we calculated differential LOCKs (dLOCKs) of H3K9me2 for six comparison categories: two representing epigenetic changes during normal myeloid differentiation (CD34+ > granulocytes and granulocytes > CD34+) and four representing epigenetic changes between AML and normal cells . The dLOCKs are ranked by their Sum Log Ratios see  reflectiFig 2), the dLOCKs did not show a substantial depletion in the gene density . Analysis of dLOCK gene intersections between the normal and AML cells helped us to answer the question whether the genome-wide changes in H3K9me2 merely reflect an interrupted differentiation process in AML or they include some genes showing gains or loss of H3K9me2 specific for the disease state. We found that, contrary to the former hypothesis that would predict complete intersection of the dLOCKs changed in the disease with those changed during myeloid differentiation, just ~38% of genes from the dLOCKCD34+>AMLA did intersect with dLOCKCD34+>granulocyte while ~51% of genes from dLOCKCD34+>AMLA intersected with dLOCKgranulocyte>AML. Reciprocally, only ~32% of genes from dLOCKAMLA>CD34+ intersected with dLOCKgranulocyte>CD34+ while ~40% of genes from dLOCKAMLA>CD34+ intersected with dLOCKAML>granulocyte . We thus conclude that AML cells, exhibit large-scale alterations (both gains and losses) in the levels of H3K9me2 that are either specific to the disease state or are transiently forming during some early pre-leukemia differentiation stages and preserved in AML.Our analysis revealed extended chromosomal domains with average size range between approximately 200 and 900 Kb. Despite the overall genome-wide correlation of H3K9me2 domains with low gene density  prompted us to analyze their selective enrichment with specific genomic features. First, we designated the conserved high (“Red”), transient (“Yellow”), and conserved low (“Green”) H3K9me2 zones by calculating the standard deviation of the 10 kb window scores of H3K9me2 in the all myeloid samples combined (see S6 Table).The observation of the conserved and variable blocks of H3K9me2 . Among the dLOCKs, the strongest difference between the CD34+ progenitors and AML is found for the “repressed” chromatin and H3K27me3 , in agreement with the genome-wide correlations . These epigenetic marks are strongly (more than 2-fold) enriched in dLOCKCD34+>AML A and depleted in dLOCKAML A>CD34+ . We also observed a notable enrichment of dLOCKCD34+>AMLA for repetitive copy number variations (CNVs). Since the last result could potentially reflect changes in DNA copy numbers rather than ChIP, we additionally analyzed the DNA annotated as repetitive CNV among our samples and observed no significant variation among all primary cells with exception of increased copy numbers in K562  in just a few genomic features: repetitive copy number variations (CNV), repressed chromatin and histone H3K27me3 . These findings suggest that the loss of histone H3K9me2 dLOCKCD34+>AMLA could cause de-repression of genes controlled by DNA methylation in AML. In contrast gain of H3K9me2 at vista enhancers within dLOCKAMLA>CD34+ would cause repression of corresponding genes in AML.The prominent specific features of the H3K9me2 blocks enriched in AML, as compared to those enriched in CD34+, are the depletion of DNA methylation sites and density of CpG islands as well as the enrichment with vista enhancers  suggesting that, in addition to transcriptional regulation, the rearrangement of large blocks of H3K9me2 in acute myeloid leukemia is linked to chromosomal translocations and genomic instability.The most universally conserved genomic features enriched in all six types of the H3K9me2 dLOCKs are the AML SNV densities confirming the association of H3K9me2 with regions of increased mutagenesis, apparently due to inhibited DNA repair in heterochromatin . In cont−6 –p<10−15) enriched with genes listed under disease or function annotation “acute myeloid leukemia” . The most prominent among the H3K9me2 blocks depleted in AML A (dLOCKCD34+>AMLA) are gene-rich clusters containing multiple repeats of ZNF genes  but very significantly (p<10B domain ) genes oAMLA>CD34+ and dLOCKAMLA>Gran) are not enriched with repeated genes and have a smaller magnitude of H3K9me2 variations (Tables D and F in S5 Table). Remarkably, they contain unique genes associated with hematological development and AML such as RUNX1, ETV6, ERG, MECOM and ETS2 among other genes (Table B in S7 Table).In contrast to the AML-depleted dLOCKs, the AML—gained dLOCKs, . In contrast, in the H3K9me2 blocks depleted in AML the most significant upstream regulators (p<10−10) were CTCF and RAD21 (cohesin), the transcriptional factors that also regulate chromosome domain boundaries. TRIM28 (KAP-1), a common co-repressor of KRAB-ZFP (ZNF) genes was prominent in the H3K9me2 blocks enriched in granulocytes . Thus, our data show that analysis of genes within differential H3K9me2 domains reveals specific regulatory pathways affected by large-scale epigenetic changes in AML.We have used Ingenuity® pathway analysis to identify upstream transcription regulatory molecules associated with coordinated changes in the dLOCKs . We found the regulatory molecule ERG standing at the top within the H3K9me2 blocks enriched in AML ). mRNA expression was assayed using Illumina HumanHT-12 array containing 33,732 hybridization probes with distinct expressed sequence tags. Of these, 7346 transcription units showed significant changes (p<0.05) between AML and control (CD34+) samples (Table C in S7 Table).To examine whether the genome-wide changes in histone H3K9me2 domains correspond to altered expression in the underlying genes, we conducted gene expression array experiments in AML cluster A cells and normal CD34+ bone marrow stem cells , suggesting that transcriptional repression of multiple genes in AML is associated with the AML-enriched H3K9me2 blocks. For the top-scoring genes associated with dLOCKCD34+>AML and upregulation in AML, Ingenuity® pathway analysis of upstream transcriptional activators revealed several transcriptional regulators including CTCF and RAF21  but not TRIM28 apparently because, although its target KRAB-ZFP genes are enriched in H3K9me2, they are known to resist silencing by G9a/GLP [We used Broad Institute gene set enrichment analysis, GSEA,  to deter G9a/GLP .AMLA>CD34+ and downregulation in AML  we found ERG as the top transcriptional regulator (P<10−5) just as it was prominent in the total dLOCKAMLA>CD34+ genes . ERG expression and ERG-regulated pathways are associated with stem cell characteristics and poor prognosis of AML [Remarkably, among the top-scoring transcriptional regulators associated with dLOCKs of AML , 66. We Fig 7A). We then conducted H3K9me2 ChIP-seq analysis of UNC0638-treated and control K562 cells as we did for the other myeloid cells. Remarkably, analysis of genome-wide correlations showed a dramatic decrease in correlation with insulators, repressed chromatin, and H3K27me3 induced by UNC0638  and recapitulating the trend observed during terminal myeloid differentiation . Accordingly, analysis of upstream transcriptional regulators revealed TRIM28 and ERG among the top transcriptional regulators in dLOCKUNC0638>K562 and dLOCKK562>UNC0638 respectively .Since G9a/GLP, the histone methyltransferase specific for H3K9me2, is involved in repression of several genes associated with AML , 25 and KRAB-ZFP (ZNF) genes most represented in dLOCKs depleted in AML but not reduced by G9a inhibition and ERG-regulated genes  residing in the dLOCKs gained in AML and strongly reduced by G9a inhibition in K562 cells . We found that transcription of KRAB-ZFP genes was not affected by G9a inhibition consistent with previous findings [MECOM gene was also not affected despite a significant loss in H3K9me2 thus showing that reduction of H3K9me2 per se is not sufficient to reverse repression of all silent genes in dLOCKs. Probably, this is due to some additional levels of epigenetic regulation, such as DNA methylation, could be established upon histone methylation [ERG and ETS1, were significantly (p < 10−8 and <10−6 respectively) activated by UNC0638 treatment . Since both of these genes are involved in AML leukemogenesis [Fig 6A) and is itself downregulated by G9a , our finding indicates that ERG may act as a part of a regulatory circuit in which its repression by G9a/GLP may lead to a decreased expression of downstream genes positively regulated by ERG and negatively by G9a/GLP-mediated H3K9me2.Next, we tested expression of selected genes residing within the transient H3K9me2 blocks by RT-qPCR in UNC0638-treated and control K562 cells. We chose genes belonging to the two regulatory pathways: TRIM28-regulated findings . Furtherhylation  to preveogenesis –71, we cFig 2). Also as expected was the correlation of the myeloid H3K9me2 domains with somatic cancer mutations [Fig 2). Correlation of H3K9me2 within different myeloid and non-myeloid samples was dramatically stronger than that between H3K9me2 vs. H3K9me3 and H3K27me2. The H3K9me2 domains in myeloid cells are thus distinct from other repressive heterochromatin marks and may play a unique role in spatial organization of the condensed facultative heterochromatin during terminal granulocytic differentiation, and inhibit chromatin access to the DNA repair processes in proliferating cells.We have mapped extensive epigenomic domains of histone H3K9 dimethylation in myeloid cells. As expected, the overall genome-wide distribution of H3K9me2 was consistent with the large genomic blocks (LOCKs) previously described in non-myeloid cells , 18 and utations  and AML-utations . RemarkaFig 8). Surprisingly, in AML cluster B as well as in leukemic K562 cells, there are comparably high levels of H3K9me2 mark at heterochromatin which, however, does not lead to an apparent chromatin condensation. This finding suggest that some developmentally-regulated factors, absent in the nuclei of AML and K562 cells, are needed to condense the facultative heterochromatin during terminal myeloid differentiation. For example, the nuclear serpins MENT (serpin B10) and MNEI (serpinB1) accumulate in the nuclei of differentiated chicken [In our previous works, we observed that H3K9me2 modification marks the relaxed chromatin in the nuclei of proliferating cells and the condensed facultative heterochromatin in the nuclei of terminally differentiated cells –21, 32.  chicken  and huma chicken , 32 granDuring normal cell differentiation, H3K9me2 is significantly increased and spreads over repressed chromosomal domains as shown for differentiating mouse lymphocytes  and stemFig 5). CpG islands were reported as the sites most strongly overlapping with H3K9me2 peaks in CD34+ hematopoietic progenitors [One of the prominent differences between the H3K9me2 blocks enriched in AML as compared to those enriched in CD34+, are the depletion of DNA methylation sites and CpG islands . The increased expression of ERG promotes hematopoietic stem cell maintenance [Our identification of the AML types with striking differences in H3K9me2 levels at dLOCKs makes it necessary to understand for which particular AML cases a pharmacological reversal of H3K9me2 domains and associated transcriptional changes could benefit or interfere with AML therapy? Here we observed that inhibition of G9a/GLP suppresses AML-specific blocks of H3K9me2 and leads to a moderate activation of the embedded proto-oncogenes ntenance , is linkntenance , 66, is ntenance , and thuntenance .At present, our study is limited by using one myeloblastic cell line, K562, derived from chronic myeloid leukemia, and total samples of CD34+ stem cells and progenitors isolated from bone marrow. While our leukemic samples were derived from peripheral blood, an alternative sources of control blood progenitors such as mobilized blood CD34+ cells or cord blood-derived CD34+ cells are also not ideal because their collection requires treatment with G-CSF [ This could result from the developmentally-regulated spreading of heterochromatin that may promote subsequent mutagenesis by inhibiting DNA damage repair [RUNX1, RUNX1T1, MECOM, ERG, ETV6, and others) at the onset of leukemogenesis may create favorable conditions for their abrupt and highly oncogenic activation by chromosomal translocations . Accumulation of large number of myeloblasts with high level of H3K9me2 at the proto-oncogenes in AML is likely to sharply increase the overall rate of mutagenesis and translocations and, therefore, the chance of AML acceleration and/or relapse. Which primary events (mutations and/or epigenetic changes) lead to the spreading of H3K9me2 blocks remains to be determined. However, our observation that the H3K9me2 blocks can be suppressed by pharmacological inhibition of the histone methyltransferase G9a/GLP  suggests that limiting H3K9me2 spreading in AML may prevent the reactivation of oncogenes resulting from the secondary AML-specific gene mutations and chromosomal translocations. Therefore, our approach to monitoring H3K9me2 levels at proto-oncogenes and regions of genomic instability may become instrumental in testing new G9a inhibitors more efficient in slowing down AML cells growth and at the same time reducing mutagenesis and preventing secondary mutations in AML. To make “epigenetic therapy” of AML and other myeloid disorders most efficient, we need to understand the fine balance within the heterochromatin-mediated mechanisms that simultaneously affect both gene expression and chromosomal stability at specific chromosomal locations during myeloid differentiation.We also noted that among the LOCKs specific for AML, there is a notable enrichment for sites that undergo chromosomal translocations in AML as well as for AML SNVs Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 TableThis file contains ten tables labeled A–J.(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.S7 TableThis file contains ten tables labeled A–D.(XLSX)Click here for additional data file.S8 Table(DOCX)Click here for additional data file.


Taken together, our findings demonstrate an important role of miR186/Twist1 axis in the regulation of PCa progression, suggesting a potential application of miR186/Twist1 in PCa treatment.Prostate cancer (PCa) is the second leading cause of cancer-related deaths in north American men, and most its related deaths are due to advanced and metastatic PCa. However, the molecular mechanisms underlying PCa progression are still unclear. Here we use a pair of prostate cell lines P69/M12, which have the same genetic background and the highly metastatic cell line M12 is a subline derived from P69, to identify the pathogenesis of PCa. We find that a key miRNA--miR186 is significantly reduced in M12 compared to that in P69. Further, we validate that miR186 is also downregulated in human PCa specimens, most significantly in the metastatic patient specimens. The low miR186 expression is correlated with poor patient survival. Through knockdown or overexpression of miR186 in PCa cell lines, we discover that miR186 strongly inhibits cell motility, invasive, soft-agar colony formation, 3D culture growth and vasculogenic mimicry (VM) formation capacity, as well as the epithelial-to-mesenchymal transition (EMT) process by downregulation of its target Twist1. Moreover, the inverse relationship between the expression levels of miR186 and Twist1 is confirmed  Prostate cancer (PCa) has become the most frequently diagnosed cancer and the second leading cause of cancer-related deaths in North American men , 2. OverMetastasis is a multistep process by which primary tumor cells undergo Epithelial–mesenchymal transition (EMT), invade adjacent tissue, enter the blood stream, survive in the circulation, extravasate into the surrounding tissue and finally form clinically detectable metastases . EMT is Twist1, a highly conserved basic helix–loop–helix transcription factor, is a key factor in promoting metastasis of cancer cells . Twist1,MicroRNAs (miRNAs) play critical roles in a variety of biological processes, including cell proliferation, development, differentiation, apoptosis, metabolism and immunity –13. AccuIn this study we found that miR186 was downregulated inmalignant PCa cell lines and clinical PCa specimens, and we experimentally demonstrated that miR186 maintained the epithelial phenotype and reduced migration and invasion, soft-agar colony formation, vasculogenic mimicry (VM) formation capability of human PCa cells through targeting Twist1, suggesting that miR186 might serve as a tumor-suppressive miRNA in the development and progression of PCa. Most importantly, one-way ANOVA analysis showed that the miR186 expression levels were statistically significant differences in subgroups clinical grade (P < 0.001), Cleason (P < 0.001), TNM stage (P < 0.01), indicating that the decreased miR186 expression contributed to PCa progression and might represent a prognostic biomarker for PCa.via selection in nude mice, undergoing DNA damage, transformation, immune escape in vivo , where ΔCt = Ct(target) − Ct(U6 or GAPDH). Each sample was analyzed in at least triplicate. The following primer sequences were used:This method was described as before . BrieflyTwist1 forward: GGAGTCCGCAGTCTTAC GAG,Twist1 reverse: TCTGGAGGACCTGGTAGAGG;GAPDH forward: AAGGTCGGAGTCAACGGA TTTG,GAPDH reverse: CCATGGGTGGAATCATATTGG AA;miR186 reverse transcription primer: GTCGTATCCAGTGCAGGGTCCGAGGTATTCGCACTGGATACGACAGCCCA;miR186 forward: GCCGGCAAAGAATTCTCC TTT,common miRNA reverse: GTGCAGGGTCCGA GGT;U6 forward: CTCGCTTCGGCAGCACA;U6 reverse primer: AACGCTTCACGAATTTGCGT.4 cells per well) were plated in a 24-well plate and then co-transfected with 200 ng of either pGreenpuro-miR186 or a pGreenpuro control, 100 ng of either pMIR-REPORTTM (AmBion) Firefly luciferase constructs containing the Twist1 3′-UTR WT or MUT, and 20 ng of pRL-SV40 Renilla Luciferase vector as a normalization control using LipofectamineTM 2000. 293T cells were collected 48 h after transfection and analyzed using the dual-luciferase reporter assay system . The pRL-SV40 vector that shows constitutive expression of Renilla luciferase was co-transfected as an internal control to correct for differences in transfection. Transfections were performed in triplicate and repeated at least three independent times.For determination of miR186 targeting Twist1 3′-UTR, 293T cells . The agar cell mixture was plated on top of a bottom layer with 0.6% agar-medium mixture in six-well plates. After 14 ~18 days, cell colonies were fixed and stained with 1 ml of 0.005% Crystal Violet for 1 hour. The photographs of the cells growing in the plate and the colonies developed in soft agar were taken, the number of colonies larger than 0.5 mm was scored by ImageJ V1.45 .The ability of anchorage-independent growth was evaluated by a soft agar assay as described . Briefly4 of cells were plated into the μ-Dish  and cultured overnight to ensure adhered. A clear area was created by removing the Culture-Insert from the μ-Dish, and photos were taken as indicated time until the wound was healed.This method for analysis of migration was conducted as described previously . BrieflyProstate cancer tissue arrays purchased from ALenabio  were deparaffinized with xylene , washed with 70%, 95% and 100% of ethanol (each for 3 times) and by two changes of DEPC-PBS buffer. Tissues were then digested with proteinase K (15 μg/ml) for 20 minutes at 37°C, rinsed 3 times with DEPC-PBS, and then air-dried.The above pretreated tissue array slides were hybridized with Digoxigenin-conjugated oligonucleotide probes for human hsa-miR186 (40 μM) for 1 hour at 37°C or at 4°C overnight, and incubated with DNase for 30 minutes at 37°C, rinsed 3 times with DEPC-PBS buffer. Following hybridization, the array slides were rinsed twice with 5×SSC, 2×SSC and 1×SSC for 5 minutes. The slides were incubated with blocking solution for 15 minutes and then with anti-DIG antibody (1:800) in 2% sheep serum blocking solution for 1 hour at 25°C. Following washes 3 times with PBS-T , slides were incubated with the alkaline phosphatase (AP) substrate (NBT-BCIP) in 10 ml of 0.2 mM Levamisole for 2 hour at 30°C in the dark. The reaction was stopped with 2 washes of AP stop solution  and 2 washes with double-distilled water. Tissue slides were counter stained with Nuclear Fast Red for 1 minute and rinsed with double-distilled water. Slides were dehydrated twice with 70%, 95% and 100% of ethanol and mounted with coverslips in Eukitt mounting medium. All images were captured and processed using identical settings.This method for analysis of migration was conducted as described previously . BrieflyParaffin-embedded sample preparation, hematoxylin and eosin staining (H&E) were performed as previously described .Luc cells [in vivo metastasis assays. 1.0×106 of each cell lines in 100 μl phosphate-buffered saline were respectively injected into the left cardiac ventricle of BALB/c nude male mice at 7 weeks old by intracardiac injection. Two weeks after the injection, the metastasis nodules was monitored every two weekly by bioluminescence imaging. Mice were anesthetized and given intraperitoneal injection of D-luciferin and 10 minutes after the injection, the bioluminescence images were taken with a charge-coupled device camera . Bioluminescence of the tissue metastases were quantified using the Living Image software. Six weeks later, the mice were killed and the metastatic nodules were dissected according to the images. Paraffin-embedded sections were then prepared and subjected to Hematoxylin and eosin staining (H&E staining). All animal studies were conducted with the approval and guidance of Shanghai Jiao-Tong University Medical Animal Ethics Committees.PC3uc cells  stably eAll statistical analyses were carried out using the SPSS 18.0 statistical software package. Comparisons of the miR186 levels in subgroups  for significance were analyzed by one-way ANOVA. 38 of PCa patients (missing 2 patient's data) were divided into 2 groups based on the miR186 expression level, the miR186-low group  and the miR186-high group  for clinical survival analysis. Survival curve was plotted using the Kaplan–Meier survival curve and analyzed by the log-rank test. The correlation between the miR186 and Twist1 levels in human clinical PCa specimens was analyzed by Pearson Correlation test and linear correlation and regression. Comparisons between groups for statistical significance were conducted with a 2-tailed Student's t-test. P<0.05(*), P<0.01(**) and P<0.001(***) were considered statistically significant in all cases.


The importance of Ca2+ to apoptosis, cell signaling, and immune activation is of special import in cancer.Although the study of calcium (Ca2+ in each of these processes vital to the initiation, spread, and drug resistance of malignancies. We describe the involvement of Ca2+, and Ca2+ related proteins in cell cycle checkpoints and Ca2+ dependent apoptosis and discuss their roles in cellular immortalization. The role of Ca2+ in inter-cellular communication is also discussed in relevance to tumor-stromal communication, angiogenesis, and tumor microinvasion. The role that Ca2+ plays in immune surveillance and evasion is also addressed. Finally, we discuss the possibility of targeting Ca2+ singling to address the most pressing topics of cancer treatment: metastatic disease and drug resistance.Here we review the current understanding of Ca2+ in cancer. By addressing Ca2+ facilitated angiogenesis, immune evasion, metastasis, and drug resistance, we anticipate future avenues for development of Ca2+ as a nexus of therapy.This review discusses the current understanding of Ca Today, Ca2+ is known to be an essential element vital to the health and function of every cell type. Amplification in the magnitude and duration of Ca2+ changes in the cytosol could mean the difference between cellular migration and cell death [2+ can signal either increased ATP synthesis or trigger cell death [2+ levels relies on an intricate symphony between a wide variety of Ca2+ channels pumps and exchangers [2+ regulation affect cancer progression, from its involvement in the immortalization of tumor cells, to its role in tumor-stromal interactions and epithelial–mesenchymal transition, and finally to current research on Ca2+ in drug resistance.Investigational interest in calcium Ca+ began oll death , 4. Simill death . This fi2+ levels, opening of intramembrane Ca2+ channels leads to an immediate influx of Ca2+ [2+ often forms complexes with calmodulin to regulate a variety of kinases and cyclins, which regulate cell proliferation and apoptosis [2+ regulates global cellular processes in such a way that any disturbances to Ca2+ homeostasis via alterations in expression or folding of Ca2+ channels and Ca2+ binding proteins can disrupt the cell-cycle [2+ levels can affect the ability of cells to regulate progression through the cell-cycle and lead to unchecked proliferation and tumorigenesis [Given the greater than ten-fold gradient between cytosolic ~ 100 nM) and extracellular (> 1 mM) Ca00 nM andpoptosis , 7. Ca2+ll-cycle . As a reigenesis , two of 2+ levels modulate the activity of guanosine exchange factor (GEF), a Ras stimulator, and GTPase activating protein (GAP), a Ras inhibitor. When activated, Ras stimulates the proliferative mitogen-activated protein kinase (MAPK) pathway, which results in upregulation of cyclin D1 in the cytoplasm, with ultimate phosphorylation of RB1 and release of the E2F transcription factor which initiates the cells transition into S-phase , as illustrated in Fig. derstood .Fig. 2Sc2+/calmodulin-dependent protein kinases (CaMKs) are also known to facilitate proliferation and avoid death by promoting passage through the cell cycle and resisting apoptotic mechanisms [Other cell cycle related families, like the Cachanisms . CaMK lechanisms –15.2+ can initiate cell death. Ca2+ flux from the endoplasmic reticulum (ER) to the mitochondria can also result in increased mitochondrial sensitivity to apoptotic stimuli. Chronic Ca2+ depletion is also known to cause ER stress and activation of stress activated protein kinases (SAPKs), which leads to apoptosis [2+ can lead to cell death by activating calpain, a cysteine protease that specifically lyses BCL2, an anti-apoptotic regulatory protein [2+ levels can help cancer cells evade the first of these pathways by interrupting the transfer of Ca2+ from the ER to the mitochondria. Specifically, Ca2+-permeable Inositol 1,4,5-triphosphate receptor (IP3R) channels that facilitate this pro-apoptotic flux of Ca2+ from the ER could be prevented form activating. This process is aided by the anti-apoptotic capabilities of BCL-2, which diminishes Ca2+ flux by binding IP3Rs or decreasing Ca2+ levels in the ER lumen [2+ to their advantage by bleeding off excess Ca2+ to create pro survival conditions. This is evident in breast cancer, where over-expression of plasma membrane calcium-ATPase 2 (PMCA2) allows for the release of Ca2+ in conditions of Ca2+ overload [2+-triggered apoptosis in tumor cells.In normal tissue, large, sustained changes to cytosolic Capoptosis . Finally protein , 17. AltER lumen , 19. Ceroverload . Potenti2, and signaling molecules necessary to support tumor growth. In pancreatic adenocarcinoma, transient receptor potential cation channel 1 and 6 (TRPC1 and TRPC6) are activated by elevated pressure and hypoxia, respectively. This process also leads to Ca2+ entry and subsequent pro-angiogenic signaling cascade [2+ sensor, stromal interaction molecule 1 (STIM1), which mediates activation of store-operated Ca2+ entry (SOCE) and leads to upregulation of hypoxia-inducible factor 1 (HIF-1) expression [2+ influx. This pathway promotes tumor progression by forming reactive oxidative species and nuclear factor kB (NF-kB). Silencing ASIC1 has been shown to reduce tumor growth and metastasis in xenograft models [2+ influx to promote epithelial–mesenchymal transition. Indeed, knockdown of ASIC1 and ASIC3 has been confirmed to suppress liver and lung metastasis in xenograft models.The cancer microenvironment consists of two interactive components: neoplastic cells and stroma . The tum cascade , 24. In pression , 26. HIFpression . In breat models . Similar2+-dependent signaling [2+-activated proliferation in endothelial cells. Upon VEGF receptor 2 activation, phosphoinositide phospholipase C (PLCγ) is phosphorylated, which in turn hydrolyzes phospholipid phosphatidylinositol -bisphosphate (PIP2), resulting in accumulation of diacylglycerol (DAG) and inositol 1,4,5-trisphosphate (IP3). Accumulation of IP3 results in increase of intracellular Ca2+ and activation of the proliferative MAPK pathway [2+ influx, leading to endothelial cell proliferation, migration and angiogenesis [Communication between tumor and stromal cells has been shown to maintain growth and expansion through Caignaling . Vascula pathway , 31. Pro pathway –34. Simiogenesis , 36.2+ dependent signaling is critical in the functioning of tumor-associated macrophages (TAMs), which have the ability to both sustain tumor growth and exert anti-tumor effects under certain conditions [2+ signaling pathway. Indeed, the expression of CCL18 in blood or cancer stroma is associated with metastasis and reduced survival [2+ influx in the immune cell, leading to lytic granule release and tumor killing. TCR stimulation can also evoke Ca2+ release from the ER via signaling cascade involving Zeta-chain-associated protein kinase 70 (ZAP-70), lymphocyte-specific protein tyrosine kinase (Lck), linker of activation of T cells (LAT), PLC-γ, and IP3 [2+ entry through Orai1 channels is required for release of lytic granules and subsequent tumor cell destruction by natural killer cells [2+ flux between the two cell types; therefore both trigger the release of tumor-killing particles at the same threshold level of Ca2+ [Canditions . TAMs insurvival . On the  and IP3 , 40. Simer cells . Lastly, of Ca2+ . Interac2+ in stromal cells to trigger subsequent secretion of mitogenic factors, which lead to proliferation and/or migration of adjacent epithelial and endothelial cells to promote angiogenesis [2+ binding protein, overexpressed in glioblastoma and thyroid, esophageal, hepatocellular, and pancreatic carcinomas, has been clinically correlated with tumor progression [2+-binding domain and a C-terminal high-affinity Ca2+-binding domain [2+ binding domains in this protein hint at a role in SPARC function, the exact pathway through which a Ca2+-SPARC complex elicits tumor advancement remains largely unknown [2+ associated TRPA1 and SPARC function identifies the needs to continued investigation into Ca2+-dependent signaling in the tumor stroma.Recent findings on transient receptor potential cation channel subfamily A member 1 (TRPA1) and secreted protein acidic and rich in cysteine (SPARC) point to areas in need of further exploration. In prostate cancer stromal cells, TRPA1 has been shown to act as a mechanosensor and have the ability to bind to Triclosan, an antibacterial agent . This biogenesis . Howevergression –47. SPARg domain . This prg domain . While t unknown . The con2+ upregulates FAK at focal adhesions through phosphorylation by the calmodulin-dependent protein kinase II (CaMKII) [2+ levels can lead to an increase in FAK and a higher turnover rate for cell–cell attachments [2+, recycles integrins in migrating cells and is another potential mediator of Ca2+-induced migration [2+, there are currently no other known differences between normal and malignant cells capable of migration [The first step in metastasis is the loss of cell–cell connections. Focal adhesion kinase (FAK) is a ubiquitously expressed cytoplasmic tyrosine kinase that increases turnover of cell–cell contacts . Overexp(CaMKII) . Thus, aachments . Calcineigration . Except igration .2+ levels affect cell–cell adhesion through TRP family proteins [2+ on ECM maintenance and remodeling remains an unanswered question, and an active area of research.Mechanical stress and intracellular Caproteins . In addiproteins . Higher proteins , 59. TRPproteins . ECM remproteins . In addi2+ signaling in some cell types [2+ levels in human breast cancer cells. Chelating Ca2+ in this instance reduced epidermal growth factor levels and blocked the induction of EMT markers. Another important contributor to proliferative ability is the SOCE system, through which Ca2+ is pumped into the cytosol when ER Ca2+ is depleted. SOCE inhibitors have been shown to inhibit migration of cervical cancer and reduce the association of focal adhesion kinases at focal adhesion sites [The epithelial–mesenchymal transition (EMT) is also associated with an increased capacity for invasion. This invasive capability has been connected to Call types . Davis ell types  have shoon sites .2+ levels have also demonstrated an effect on the re-differentiation of epithelial breast cancer lines. Re-differentiation after metastasis, is important in allowing cancer to survive in a novel niche after metastasis. Although physiological levels of Ca2+ inhibit proliferation and invasion, higher than normal extracellular levels increase estrogen receptor activity, which has been associated with more aggressive and invasive breast cancers [2+ levels ultimately increase the risk of bony metastasis in both breast and prostate cancer [Extracellular Ca cancers . High exe cancer .2+ signaling is involved in every step of this process [2+ signaling to prevent metastasis is challenging, as any inhibition is likely to impact normal cells as well. Coupling Ca2+ to a cancer specific target has been shown to reduce normal cell death in a prostate cancer study [2+-ATPase (SERCA) inhibitor, with the targeting peptide for a prostate-specific antigen was able to limit cell death to prostate cancer cells while sparing normal cells [2+-dependent migration mechanisms between normal and cancerous cells are similar enough that another mode of targeting Ca2+ should be considered [2+-dependent signaling, such as proteins associated with cell–cell contacts and ECM degradation, may be a more practical approach [Tumor metastases cause the majority of cancer deaths. As such, development of preventative measures against and treatment of metastasis is an extremely active area of research. Metastatic transformation requires the loss of epithelial cell–cell connections and the transformation of primary tumor cells into a migratory mesenchymal cell. During this process, the cells must also degrade the ECM, cross basement membranes, and enter the circulatory system. As detailed above, Ca process –68. Therer study . For exaal cells . Despitensidered . As we happroach .2+ might also play a significant role in facilitating drug resistance. In a recent study on breast cancer cell lines, increased mRNA levels of plasmalemmal Ca2+ efflux pump (PMCA2), which removes Ca2+ from the cell, was correlated with poor survival [In addition to being implicated in the described processes of tumor progression, Casurvival . Silencisurvival .P-glycoprotein or multidrug resistance protein 1 (MDR1), an ATP-dependent efflux pump that expels cytotoxic drugs, has also been associated with chemotherapeutic resistance in breast cancer [2+-permeable channel TRPC5 in adriamycin-resistant breast cancer cell lines. In both human and mice models, TRPC5 expression is often higher in tumor cells and concentrated to vesicles. Indeed, in the adriamycin-resistant breast cancer study, suppressing the activity of pro-oncotic TRPC5 reduced MDR1 induction and reversed adriamycin resistance both in vitro and in vivo [t cancer . Inducti in vivo . TRPC5 s2+ signaling and drug resistance in HCC. In this study, inhibition of Ca2+ signaling via TRPC6 inhibition resulted in restored sensitivity of HCC cells to various chemotherapeutic drugs and attenuation of the epithelial–mesenchymal transition [2+ mediated drug sensitivity. Namely, reduction of intracellular Ca2+ via TRPC6 inhibition activates STAT3, which then stimulates re-differentiation of cells and restores drug sensitivity [2+ channels have also been associated with drug resistance in ovarian and other high-morbidity gynecological malignancies. Experiments on mice models of ovarian cancer have shown mibefradil inhibition of T-type Ca2+ channels to sensitize the disease to carboplatin. Furthermore, both pharmaceutical and genetic inhibition of Ca2+ channels led to apoptotic growth suppression in the ovarian cancer cells [A subtype of TRPC6 has also been implicated in another malignancy infamously recalcitrant to multiple chemotherapeutic regimens, hepatocellular carcinoma (HCC). A recent study has shown that a subtype of TRPC6, usually expressed at low levels in normal hepatocytes, mediates Caansition . These isitivity . T-type er cells .2+-mediated signaling can restore drug sensitivity in breast, colorectal, hepatocellular, and ovarian cancers suggests a possible role for Ca2+ channel blockers as an adjuvant therapy to standard-of-care chemotherapies.Drug resistance, especially the development of multi-drug resistant disease, is of special concern in cancer therapy. The fact that Ca2+ signaling is intrinsic to all aspects of cancer biology , isolation of the specific effects remains elusive. This suggests development of therapies targeting Ca2+ should be constructed using experience from other “undruggable” targets like Ras and Myc. Instead of targeting Ca2+ itself, known Ca2+ associated proteins such as PMCA2, TRPC5, and MDR1 may serve as more discerning objectives.From tumor initiation to metastasis and drug resistance, Caogy Fig. . Ironica2+ signaling is immunotherapy. Recent publications have suggested that calcium signaling could be used to improve the efficiency of immunotherapy approaches by enhancing antigen presentation and in the adaptive immune response. In addition, the role of Ca2+ in killing by natural killer cells and cytotoxic T lymphocytes may also be exploited as high levels of intracellular Ca2+ are required for efficient cancer cell killing activity. Conversely, Ca2+ reduction has been showing to reduce growth of malignant cells themselves. Thus, it is necessary to identify the specific Ca2+ channels utilized in granule exocytosis so that immune system’s ability to kill malignant cells can be enhanced without simultaneously promoting tumor growth. Although immunotherapy is a promising field through which Ca2+ signaling could augment treatment efficacy, the ubiquity of Ca2+ in normal metabolism and cellular function makes greater understanding of specific mechanisms in Ca2+ signaling necessary before such dreams become attainable.Another emerging field of interest for Ca


The ability to respond to injury with tissue repair is a fundamental property of all multicellular organisms. The extracellular matrix (ECM), composed of fibrillar collagens as well as a number of other components is dis-regulated during repair in many organs. In many tissues, scaring results when the balance is lost between ECM synthesis and degradation. Investigating what disrupts this balance and what effect this can have on tissue function remains an active area of research. Recent advances in the imaging of fibrillar collagen using second harmonic generation (SHG) imaging have proven useful in enhancing our understanding of the supramolecular changes that occur during scar formation and disease progression. Here, we review the physical properties of SHG, and the current nonlinear optical microscopy imaging (NLOM) systems that are used for SHG imaging. We provide an extensive review of studies that have used SHG in skin, lung, cardiovascular, tendon and ligaments, and eye tissue to understand alterations in fibrillar collagens in scar tissue. Lastly, we review the current methods of image analysis that are used to extract important information about the role of fibrillar collagens in scar formation. The ability to respond to injury with tissue repair is a fundamental property of all multicellular organisms. In the seconds after injury, various intracellular and intercellular pathways must be activated and synchronized to respond if tissue integrity and homeostasis are to be restored. In general, the wound repair process in almost all tissues involves activation of the cellular components of the immune system , the blood coagulation cascade and the resultant activated inflammatory pathways. In addition to immune cells, multiple structural cell types are activated , which undergo marked changes in phenotype and gene expression leading to cell proliferation, differentiation, migration and extracellular matrix production ,2. Once Demographically, the number of individuals suffering from chronic wounds and impaired healing conditions continues to rise leading to health and economic burdens to society ,7,8,9. AStudying wound repair in various conditions and models will expand our understanding of the wound repair process in humans that will hopefully lead to the identification of novel pathways or molecular signals that can be therapeutically targeted to restore their lost regenerative capacity. Over the last 15 years, nonlinear optical microscopy (NLOM) has emerged as a powerful research tool ,11,12,13In this review, we describe the physical characteristic of SHG, and the current NLOM systems that are used by biologists for SHG imaging. We provide an extensive review of studies that have used SHG in wounding and repair of skin, lung, cardiovascular, tendon and ligament, and eye tissues to understand alterations in fibrillar collagens in scar tissue ,40,41,42The extracellular matrix (ECM) is essential for the normal development, function and homeostasis of all eukaryotic cells ,44,45,46Collagens form a heterogeneous family of fibrous proteins of which there are 28 different types identified in vertebrates. In animals, the collagen family represents the most abundant protein  and collAt the structural level, all collagen molecules are made up of three polypeptide peptides ,53,54,55operties ,58,59,60SHG microscopy has emerged as a useful tool for studying key facets of collagen remodeling. SHG imaging is an attractive alternative to conventional or fluorescent-based histology for studying tissue composition and visualizing the molecular structure of collagen due to its label-free nature, high sensitivity and specificity ,61,62,63In short, SHG is a process that occurs when two photons are combined in an optically nonlinear medium, lacking in centro-symmetry (such as collagen), creating a SHG photon with a wavelength exactly half of the excitation wavelength  is the linear susceptibility . The linear susceptibility due to an applied electric field indicates the degree of polarization of a dielectric material. A material with a higher linear susceptibility, has a greater ability to polarize in response to the field, thereby reduces the total electric field inside the material (and stores energy).The optical response of a material is expressed in terms of the induced polarization. Polarization describes the response of both the material and the applied electric field to one another. Polarization can be used to calculate the forces that result from these interactions ,65,66. FP in powers of the electric field E. The second term defines the SHG.In nonlinear optics, such as SHG imaging the response of the material is often described as a polynomial expansion of the material polarization The SHG signal originates from the nonlinear polarization. The incident wave generates dipoles inside the material. These dipoles radiate at twice the frequency of the incident wave. The relative phase of the induced dipoles is fixed because the incident beam has a well-defined amplitude and phase within the material at any given point and time. The SHG signal can be obtained only if the induced dipoles radiate in phase, as illustrated in There are several factors affecting the magnitude of SHG. It depends quadratically on the intensity of the excitation light, and is affected by the polarization and wavelength of the excitation light. SHG signal can also be dependent on the inherent properties of the material: the nonlinear susceptibility, the phase mismatch between the SHG and the excitation light, and the distribution and orientation of the SHG sources within the focal volume ,68,69,70Collagen fibres have a very suitable structure for generating SHG signal. Fibrillar collagen is highly anisotropic and the SHG signal generated is coherently amplified because of the tight alignment of repeating structures within the collagen triple helix and within fibrils. As SHG imaging is dependent on the signal remaining phase-matched within the material, a second harmonic wave generally co-propagates with the excitation beam, resulting in SHG signal in the same, forward direction as the excitation beam ,69,71. TA single, 40- to 300-nm collagen fibre would be expected to behave as a single dipole, which radiates in all directions except normal to the incident beam. The peptide bonds within the collagen chains generate a permanent dipole moment, which is a measure of the separation of positive and negative electrical charges within a system, allowing SHG to occur within collagen-rich samples, as shown in An interesting characteristic of SHG microscopy is that the excited volume within the specimen is elliptical, with the long axis in the direction of the beam. In a collagenous tissue, the overall signal is predominantly propagated in the forward direction, compared to an isolated individual fibre that may radiate SHG signal both forward and backward. Any group of collagen fibres will have more excited dipoles in line with the beam than across it.An important aspect to consider is that SHG is polarization sensitive. For many sources of SHG, the amount of signal produced is dependent on the polarization state of the incident laser light, relative to the scattering due to the molecular structure. To illustrate this, we shall focus on the polarization sensitivity of SHG from collagen fibrils, as it is the component most imaged by SHG microscopy in biomedical applications ,13,72,73Most studies on the polarization sensitivity of collagen have been carried out on tendon which is composed of highly ordered parallel collagen-type I fibres. The intensity of the SHG signal produced from a collagen sample is dependent on the orientation of the polarization state of the laser excitation light with respect to the fibre axis ,73,74, aFor fibrils lying in the plane perpendicular to the direction of excitation laser light propagation, the amount of SHG produced depends on the angle , and therefore detect the signal generated from all fibres within the tissue, independent of their orientation.In SHG microscopy the focal area in which the SHG signal is generated has sub-micron dimensions, which is much smaller than the coherence length in collagen. Therefore, the SHG signal should not be significantly reduced by destructive interference. SHG microscopy has proven to be an ideal tool for the analysis and quantification of the spatial arrangement of collagen fibres in tissue ,72,73,74There are a number of commercial multi-photon confocal microscopes now available on the market that can be used for SHG imaging . In general, whether using in-house developed or ready-made equipment, a similar set up is used, as reviewed extensively previously  and showMultimodal nonlinear optical (NLO) laser-scanning microscopes have been key to visualizing several specific biomolecules without the need of any specific tissue preparation and providing superior spatial and biochemical specificity. Coherent anti-Stokes Raman scattering (CARS), stimulated Raman scattering (SRS), two-photon-excitation fluorescence (TPEF), SHG and third harmonic generation (THR) have been extensively used in biomedical research. However, one of the biggest challenges faced by scientists are related to miniaturizing these laser-based microscopes to a point where these techniques could be easily used in clinic and in vivo.Several groups have been intensively working towards this goal ,77,78. CFinally, another recent application of miniaturized SHG was proposed by Schnitzer et al. ,83. TheySHG imaging has been used to study a number of tissues and assess the quality of the fibrillar collagen in both the normal and disease state. In The skin is composed of three main layers: the epidermis, dermis and hypodermis. The epidermis is a thin layer of epidermal cells covered by the stratum corneum and provides the barrier function of the skin. The deeper dermal layer is primarily collagenous and provides structural support for cells and the dermal appendages , as well as the mechanical properties  of the skin . A largeRecent studies have used SHG to distinguish between normal and pathologically scarred skin, suggesting potential diagnostic use for SHG imaging in the clinic ,103. StuThe lung is formed from a dichotomous branching structure of airways that enables airflow that enters the nose and mouth to be directed to the 600 million terminal alveoli structures where gas exchange occurs. In terms of fibrillar collagens, the developing lung contains primarily fibrillar collagens I and III, which are deposited primarily by lung fibroblasts during the canalicular stage, in which the respiratory airways and alveolar ducts are formed, preceding the bulk of elastogenesis ,109. FroTo date, SHG imaging of fibrillar collagen has primarily been used to confirm fibrotic regions in human IPF tissues  and mousArteries are mainly composed of soft collagenous tissue; they serve as an elastic reservoir to transform the high pressure, pulsatile output into a flow with moderate fluctuations . The vesIn addition to arteries, SHG imaging of collagen has been used for the characterization of cardiac scar tissue formed due to myocardial infarction . MostaçoTendons and ligaments facilitate a wide range of joint motion and considerable weight and energy savings associated with locomotor movement ,126. TenThe stroma of the eye is composed mainly of collagen type I, however common methods that are used for imaging the corneal epithelium  are ineffective for imaging this collagenous tissue ,133. FurCellularized collagen gels are a common model used to understand several biological processes involving the interactions of cells with collagen ,134,135.SHG microscopy has been a very powerful tool in biomedical research. However, most published SHG imaging work has described collagen organization without focusing on the quantitative measures which are possible to implement to characterize SHG images. In several studies, pathological conditions were described using empirical observations derived from collagen SHG images. While the ability to track associations between collagen SHG images and pathology is important, it is equally important to have the ability to track such correlations using quantifiable measures for objective comparison. Quantitative SHG imaging analysis methods have largely relied on image pixel-counting techniques, similar to those applied to histological tissue images. Several SHG collagen imaging studies have recently proposed novel methodologies for quantifying the features of SHG images.Although commercially available laser scanning microscopes are supplied with software with some rudimentary data analysis capabilities, many groups have been working on developing methods to quantify the fibrillar structures detected in SHG images. Many external software packages have been successfully used for analysis of SHG data, including the measurement of intensities, the application of a threshold for measuring fibre lengths and division for F-SHG/B-SHG analysis. ImageJ or Fiji can run these analyses, or the can be automated using MATLAB or LabVIEW. Commercial packages including Improvision and Imaris are capable of rendering 3D images, as are some plugins especially written for Fiji. We present below the most commonly used analysis methods for SHG data; however, we would like to note that, while these processes are integral to measuring fibre length and distribution, they are not specific to SHG image analysis.Intensity-based image analysis is the most straightforward form of quantification. The signal collected in each individual detector is associated with a specific pixel. Each pixel receives a value which can be associated to the signal intensity, and therefore, the amount of collagen deposited in that specific region. It is important to highlight that intensity-based analysis takes into account the intensities of individual pixels, and they are considered independently from their neighboring pixels . Other tTo exploit the coherence of SHG and thus extract sub-resolution feature information, the SHG microscope could be set up with both F-SHG and B-SHG collection channels. The microscope’s transmission pathway enables us to collect the F-SHG signal. This mode allows one to collect the majority of the SHG signal. To acquire B-SHG, the use of the confocal laser scanning head is necessary. It is important to highlight that to distinguish between TPEF and SHG signal it is necessary to perform a synchronous spectrum. In terms of quantitative analysis, the structural differences observed between the F-SHG and B-SHG images have not been well studied . F-SHG/BPolarization-resolved SHG is an alternative that can be used to extract information beyond simple visualization of fibre lengths or by pixel intensity. Polarization-resolved SHG is a form of measurement, which analyses the signal intensity as a function of laser polarization. Examples of this type of SHG measurement have been presented by some authors ,138, wheAs the SHG signal generated by collagen fibres is highly dependent on their orientation, when working with polarization-resolved SHG, one can easily create a gamut of images showing the preferred fibre orientation within a certain region. As a general guideline, in the first measurement, the laser polarization is aligned with the long axis of a collagen fibre(s), and then rotated through 180Another way to quantitatively extract information from SHG images is by applying transform-based image analysis techniques. These techniques represent an image in a space whose coordinate system has an interpretation that is closely related to the characteristics of a texture, using the spatial frequency properties of the pixel intensity variations. Several methods are available and the success of these methods will strongly depend on the type of transform used to extract textural characteristics from the image and the final goal of the overall analysis. Methods based on Fast Fourier Transform (FFT) usually perform poorly in practice, due to its lack of spatial localization. However, Indhal and Næs  illustraTexture analysis has always been a powerful tool in the analysis of bio-medical imaging, remote sensing and industrial inspection, and its outputs are mainly classification, segmentation, and synthesis. Textures are very diverse and the approaches for analyzing them are likewise very diverse, and mainly differ from each other by the method used for extracting textural features. Texture analysis techniques, also called higher order statistics, primarily describe characteristics of regions in an image through higher-order measures of their grayscale histograms. The most robust and frequently cited method for texture analysis is based on extracting various textural features from a gray level co-occurrence matrix (GLCM) . The GLCThere is no question that SHG microscopy is a powerful tool for examining biological tissue. However, as with any technology, it also presents limitations. As is the case with other NLOM modalities, SHG needs a laser as a light source. Most of the commercial femto-seconds lasers  are based on Ti:Sapphire laser sources. The price of Ti:Sapphire lasers have decreased over the years, but are still quite an investment. One recent advance in this regard is the use of solid-state pump lasers, as they are less expensive, more compact and reliable sources for NLOM.Another major factor that significantly affects making SHG microscopy applicable for broader use is the availability of compact systems small enough to fit into a catheter-sized probe that can be used to acquire in vivo images, as well as fully automated and maintenance-free systems. This next step for laser and NLOM development will allow these techniques to be used in routine, biological and clinical environments without the need for laser physicists.The limited penetration depths . To date there are no methods available that can distinguish between fibrillar collagen types, which could greatly advance the field of wound repair and regeneration biology.Understanding scar formation (fibrillar collagen formation) over time in humans has huge potential to deliver new therapeutics for correct wounds. Without the need for labeling, SHG imaging is particularly suitable for in vivo studies of collagenous connective tissue, partially due to strong contrast and large sensing depth. In future, the development of SHG endoscopes comprised of a pulsed laser source, a fibre-optic catheter, and a microelectromechanical systems (MEMS)-based scanning head, could offer large potential to clinical research. This would enable achievable penetration depths of 100–200 micrometers to analyze scar tissue non-invasively in human subjects using current clinical endoscopy techniques. Such a device could aid in assessment of scar tissue and enable new protocols to non-invasively monitor the efficiency of therapeutics and their effects on tissue function in vivo.