Cyclic Electromagnetic DNA Simulation (CEDS) targeting Telomere Repeat Sequence can enhance Anticancer Effect, while CEDS targeting Canonical E-box Sequence induce Oncogenic Effect in Cells

Cyclic electromagnetic DNA simulation (CEDS) was used in the previous study ( 1) to stimulate the base pair polarities of oligo-dsDNAs, plasmid DNAs, and miRNAs. This study applied dodecagonal CEDS to target telomere repeat sequence (TTAGGG*-CEDS), canonical E-box sequence (CACGTG*-CEDS) in genomic DNA of RAW 264.7 cells and KB cells. During cell culture, CEDS was performed at 20-25 Gauss for 20 min, and followed by cytological observation and immunoprecipitation high-performance liquid chromatography (IP- HPLC) using 350 antisera. KB cells treated with TTAGGG*-CEDS showed a significant decrease in cell density and metachromasia in toluidine blue staining compared to untreated control, while only a slight decrease in cell density and metachromasia was observed by telomere mutation sequence, TTTGGG*-CEDS. Conversely, CACGTG*-CEDS induced almost no change in cell density, cell number, metachromasia in toluidine blue staining compared to random sequence*-CEDS (2(ACGT)*-CEDS) and untreated control. IP-HPLC results showed that TTAGGG*-CEDS induced a potent anticancer effect by downregulating RAS, oncogenesis, and telomere signaling, and activating NFkB signaling-p53 - and FAS-mediated apoptosis-innate and cellular immunity signaling axis compared to untreated control and positive control performed with nonspecific poly- A 12A*-CEDS. In contrast, CACGTG*-CEDS exhibited a significant oncogenic effect by enhancing of RAS and NFkB signaling and resulting oncogenesis-glycolysis-chronic inflammation signaling axis. Therefore, it is suggested that CEDS is able to target DNA motif sequences in genomic DNA, and that TTAGGG*-CEDS and CACGTG*-CEDS are favorable candidates to regulate important genes involved in oncogenesis, inflammation, apoptosis, etc.

Cyclic electromagnetic DNA simulation, Telomere, E-box, Protein signaling pathways (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 3

The previous study showed that CEDS increased DNA hybridization potential and influenced the functions of six bps double-stranded DNA (dsDNA), 24 bps dsDNAs, plasmid DNAs, and miRNAs through in vitro experiments (1). In the same line, this study demonstrated CEDS targeting DNA motif sequences in genomic DNA. To increase the efficiency of CEDS, this study employed both strands of DNA motif sequences, which were designated as "target sequence*-CEDS." Telomere repeat sequences facilitate the replication of chromosome ends and the generation of a T-loop with a telomere-binding protein complex, shelterin, to prevent chromosomal degradation. Telomere shortening and instability can induce aging and various diseases due to telomere dysfunction and chromosomal instability (2). Furthermore, they can form G-quadruplex structure with external Hoogsteen bonding strength ( 3), which plays an important role in chromatin protection, DNA replication, transcription, and genomic stability. In this study, a telomere repeat sequence, dsTTAGGG, was selected for CEDS. The E-box binding proteins play a pivotal role in regulating transcription activity for genome-wide transcription of numerous genes. Their numbers and types vary depending on the binding specificity of E- box (4). Among the consensus sequences of E-box, dsCANNTG, the canonical E-box sequence dsCACGTG, which is known to be preferentially bound by cMyc, was selected in this study for CEDS to know the transcriptional changes of cMyc target genes. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 4 Cytological observation of KB cells treated with CEDS using a telomere repeat sequence The KB cells derived from human epithelial cell (ATCC, USA) were cultured on culture dishes (SPL, Korea) in Dulbecco’s modified Eagle’s medium (WelGene Inc., Korea) supplemented with 10% fetal bovine serum (WelGene Inc., Korea), 100 units/mL carbenicillin, 100 μg/mL streptomycin, and 250 ng/mL amphotericin B (WelGene Inc., Korea), in 5% CO 2 incubator at 37.5°C. Approximately 50% confluent KB cells grown on culture dish surfaces were treated with dodecagonal CEDS using a telomere repeat sequence*-CEDS (TTAGGG*-CEDS) at 23-25 Gauss for 20 min twice a day. Following three days of experiments, the cells were fixed with 10% buffered formalin and stained with hematoxylin and eosin (H&E). TTAGGG*-CEDS exhibited a notable reduction in cell density on the culture dish as observed visually, and a comparable decline in the number of KB cells as observed microscopically, in comparison to untreated control and CEDS using a random sequence 2(ACGT)*-CEDS. In the high-magnification, the cells treated with TTAGGG*-CEDS exhibited notable reduction in cell number, accompanied with frequent pyknotic cells undergoing apoptosis compared to the cells not treated with TTAGGG*-CEDS and the cells treated with 2(ACGT)*-CEDS (Fig. 1). (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 5 Figure 1. Cytological observation of KB cells. H&E stain. Visual and microscopic view of cells treated with TTAGGG*-CEDS (D-F), 2(ACGT)*-CEDS (G-I), or no CEDS (A-C). F: Noted severe apoptosis with increased empty space. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 6 Cytological observation of KB cells treated with CEDS using a telomere repeat sequence or a canonical E- box sequence KB cells were cultured on plastic dishes as described above. Approximately 50% confluent KB cells grown on culture dish surfaces were treated with dodecagonal CEDS using a target sequence at 20-25 Gauss for 20 min twice a day in the culture incubator. Following three days of experiments, the cells were fixed with 10% buffered formalin and stained with toluidine blue, a basic thiazine metachromatic dye with high affinity for acidic tissue components, likely DNA and RNA. Subsequently, visual and microscopic observations were performed. A comparison of CEDS effect between telomere repeat sequence*-CEDS (TTAGGG*-CEDS) and mutant telomere repeat sequence*-CEDS (TTTGGG*-CEDS) revealed that KB cells were significantly decreased in cell density and metachromasia in toluidine blue by TTAGGG*-CEDS compared to untreated control, while only a slight decrease by TTTGGG*-CEDS (Fig. 2 A-C). The results showed that TTAGGG*-CEDS strongly induced cell death, while TTTGGG*-CEDS induced cell death to a lesser extent than TTAGGG*-CEDS due to a base pair inversion from A-T to T-A. On the other hand, CACGTG*-CEDS induced almost no change in cell density, cell number, metachromasia in toluidine blue staining both visually and microscopically compared to 2(ACGT)*-CEDS and untreated control (Fig. 2 D-F). (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 7 Figure 2. Cytological observation of KB cells treated with CEDS at 20-25 Gauss, twice daily for 20 min, during 3 days of cell culture with toluidine blue stain. For the comparison of CEDS-induced cytological results, TTAGGG*-CEDS and TTTGGG*-CEDS were assessed compared to no CEDS (A- C), and CACGTG*CEDS was compared with 2(ACGT)*-CEDS and no CEDS (D-F). (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 8 IP-HPLC analysis for CEDS-induced changes of protein signaling pathways in RAW 264.7 cells IP-HPLC has been developed to analyze the protein expression levels in comparison with the controls ( 5, 6). The immunoprecipitated proteins were subjected to the analysis with a HPLC (Agilent, USA) using a reverse phase column packed with non-adherent silica beads. The control and experimental samples were analyzed in sequence to permit a comparison of their HPLC peaks. IP-HPLC is available to use only small amount of total protein, up to 20-50 μg, thereby it can detect wide range of protein signaling simultaneously and repeatedly even with the limited amount of protein sample. However, IP-HPLC can provide the protein expression level in a simple, fast, accurate, cheap, multiple, and automatic way compared to other ordinary protein detection methods. In addition, the IP-HPLC data are available for statistical analysis. The RAW 264.7 cells, derived from monocytes/macrophage-like cells of Balb/c mice, were utilized by limiting their culture passage number to less than 20 (7). The cells were cultured in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum, 100 units/mL carbenicillin, 100 μg/mL streptomycin, and 250 ng/mL amphotericin B (WelGene, Korea), in 5% CO 2 incubator at 37.5°C. The cell culture product containing 108-109 cells was placed in the incubator and treated with dodecagonal CEDS using a target sequence at 20-25 Gauss, 5% CO2, and 37℃ for 20 minutes, left in the incubator for another 30 minutes, and harvested by centrifugation at 150g for 10 min for the following IP-HPLC assay. The RAW 264.7 cells were lysed using protein lysis buffer (iNtRON Biotechnology, Korea), and analyzed by IP-HPLC as follow. Protein A/G agarose columns were separately pre-incubated with each 1 μg of 350 antibodies (Table S2). The supernatant of the antibody-incubated column was removed, and followed by IP- HPLC. Briefly, each protein sample, 50-100 μg, was mixed with 5 mL of binding buffer (150mM NaCl, 10mM Tris pH 7.4, 1mM EDTA, 1mM EGTA, 0.2mM sodium vanadate, 0.2mM PMSF and 0.5% NP-40) and incubated in the antibody-bound protein A/G agarose bead column on a rotating stirrer at room temperature for 1 h. After multiple washing of the columns with Tris-NaCl buffer, pH 7.5, in a graded NaCl concentration (0.15–0.3M), the target proteins were eluted with 300μL of IgG elution buffer (Pierce, USA). The immunoprecipitated proteins were analyzed using a precision HPLC unit (1100 series, Agilent, Santa Clara, CA, USA) equipped with a reverse-phase column and a micro-analytical UV detector system (SG Highteco, Hanam, Korea). Column elution was performed using 0.15M NaCl/20% acetonitrile solution at 0.5 mL/min for 15 min, (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 9 40˚C, and the proteins were detected using a UV spectrometer at 280 nm. The control and experimental samples were run sequentially to allow comparisons. For IP-HPLC, the whole protein peak areas (mAUs*) were obtained and calculated mathematically using an analytical algorithm by subtracting the negative control antibody peak areas, and protein expression levels were compared and normalized using the square roots of protein peak areas. IP-HPLC is available to use only small amount of total protein, up to 20-50 μg, thereby it can detect a wide range of protein signaling simultaneously and repeatedly even with the limited amount of protein sample. Since IP-HPLC gives the relative ratio (%) of protein expression compared to untreated control, the protein expression data could be analyzed statistically and widely compared with other protein expressions. The ratios were divided into five categories; severe underexpression (below 80%), marked underexpression (80%-below 95%), minimal change (95%-below 105%), marked overexpression (105%-120%), and severe overexpression (above 120%). Although the immunoprecipitation is unable to define the size-dependent expression of target protein compared to western blot, it collects every protein containing a specific epitope against antibody in the protein samples from cells, blood, urine, saliva, inflammatory exudate, etc. ( 5, 6, 8-17). Therefore, IP-HPLC can detect whole precursor and modified target proteins similar to enzyme-linked immunosorbent assay (ELISA), but the antigen-antibody binding strength can be adjusted by different salt buffers depending on the condition of the protein samples. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 10 Telomere repeat sequence*-CEDS induced potent anticancer signaling in RAW 264.7 cells IP-HPLC results showed that TTAGGG*-CEDS upregulated 34 proteins (31.6%), downregulated 67 proteins (62.6%), and exhibited minimum effect on six proteins (5.6%) out of 107 telomere-associated proteins observed in this study. In addition, The TTAGGG*-CEDS affected the overall protein signaling pathways in RAW 264.7 cells by downregulating telomere-associated proteins and reactive proteins as well (Fig. 3A, Table 1), which were summarized as follows according to the expression of telomere-associated proteins. Proliferating signaling was suppressed by downregulating Ki-67 (87.9%), PCNA (82.9%), CDK4 (82.9%), p21 (89.8%), nucleolin (92.8%). cMyc/MAX/MAD network was suppressed by downregulating MAX (92.8%). Wnt/β-catenin signaling was suppressed by downregulating TCF1 (85.2%), Snail1 (78.1%). P53/Rb/E2F1 signaling was suppressed by downregulating p53 (77%), Rb1 (93.2%), CDK4 (82.9%), E2F1 (83.3%). Protein translation signaling was suppressed by downregulating DOHH (89.8%), eIF2α (91.5%). MiRNA biogenesis signaling was suppressed by downregulating AGO2 (82%). Growth factor signaling was partially suppressed by downregulating EGFR (90%), IGF1 (85.8%), TGF β3 (78.5%), Met (90.9%). Cytodifferentiation signaling was partially suppressed by downregulating Ep-CAM (85.5%). RAS signaling was suppressed by downregulating, NRAS (79.6%), PI3K (88.9%), PTEN (79.1%), AMPKα (82.5%), JAK2 (89%), PKC (86.4%). ER stress was suppressed by downregulating eIF2α (91.5%), GADD153 (85%), p-GADD153 (91.3%), IRE1α (94.3%), LC3β (91.7%). Survival signaling was suppressed by downregulating SP1 (72.4%), sirtuin6 (85.2%). Acute inflammation signaling was suppressed by downregulating IL1 (93.2%), MCP1 (90.5%), CRP (90.7%). PARP-mediated apoptosis signaling was suppressed by downregulating, PARP1 (94%), c-PARP (93.8%). Fibrosis signaling was suppressed by downregulating collagen 3A1 (90.9%), FGF1 (82.9%), laminin α5 (93.9%), integrin α5 (89.2%), integrin β1 (86.9%), α1-antitrypsin (91.6%), tenascin C (91.3%). Senescence signaling was suppressed by downregulating klotho (85.1%), sirtuin6 (85.2%), p21 (89.8%). Telomere signaling was suppressed by downregulating TERT (88.3%), TRF1 (89.9%), TIN2 (69.3%). (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 11 Conversely, Notch/Jagged signaling was activated by upregulating Notch1 (109.6%). Osteogenesis signaling appears to be activated by upregulating BMP2 (107.4%), BMP3 (133.2%), BMP4 (115%), RUNX2 (106.5%), OPG (112%), RANKL (122.1%). Neuromuscular differentiation signaling was activated by upregulating NSEγ (120.4%), GFAP (106.2%), NK1R (111.1%), S100 (109.1%), αSMA (106.1%). NFkB signaling was activated by upregulating NFkB (112.4%), p38 (118.1%), mTOR (113%) . Protection signaling was activated by upregulating HSP27 (135.8%), HO1 (128%), FOXO3 (125.9%), NRF2 (124.1%), HSP70 (121%), GSTO1/2 (107.3%). Angiogenesis signaling was activated by upregulating VEGFA (111.9%), FGF2 (106.4%). Innate immunity signaling appears to be activated by upregulating lactoferrin (110.1%), CAMP (125.8%), β-defensin1 (109.6%), β-defensin2 (111%), TLR2 (108.1%), elafin (118.5%). Cellular immunity signaling was activated by upregulating CD44 (129.7%). Chronic inflammation signaling was activated by upregulating IL6 (123.4%), IL10 (112.5%), COX2 (133%). P53-mediated apoptosis signaling appears to be activated by upregulating p73 (106.1%), PUMA (113.8%), NOXA (111.7%), c-caspase9 (111.1%), caspase3 (130.3%). FAS-mediated apoptosis signaling was activated by upregulating FAS (115%), BID (114%), caspase8 (109.6%), caspase3 (130.1%). Glycolysis signaling was activated by upregulating LDHA (117%), GAPDH (111.1%). In addition, TTAGGG*-CEDS variably influenced epigenetic modification signaling by upregulating proteins involved in DNA methylation/acetylation such as KDM4D (107.1%), MBD4 (112.4%), HMGB1 (116.3%), therefore, it induced a trend towards an increase in the methylation of histones and DNAs, transcriptional repression. TTAGGG*-CEDS broadly affected oncogenesis signaling by upregulating such as BRCA1 (126.5%), cMyb (127.7%), ATM (118.2%), YAP1 (111.6%), PIM1 (108%) , significantly impacting the entire protein signaling pathways in RAW 264.7 cells. In addition to the expressions of telomere-associated proteins, the expressions of telomere-unassociated proteins in the cells treated with TTAGGG*-CEDS showed similar trends to the above protein signaling (Fig. 3, Table 1). Resultantly, TTAGGG*-CEDS primary inhibited RAS signaling, subsequently inactivating protection-ER stress-survival signaling axis, p53- and FAS-mediated apoptosis signaling axis , and telomere-oncogenesis- PARP-associated apoptosis-fibrosis axis, while activated NF-kB signaling, subsequently stimulating (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 12 epigenetic modification-protection-angiogenesis signaling axis, p53- and FAS-mediated apoptosis-glycolysis- chronic inflammation signaling axis (Fig. 3B). The results indicate that TTAGGG*-CEDS induced potent anti-oncogenic effect with extensive apoptosis on RAW 264.7 cells by inhibiting cell proliferation, ER stress, survival, cellular senescence, telomere instability, and oncogenesis, and concurrently enhancing ROS protection, angiogenesis, apoptosis, glycolysis, and chronic inflammation. It is noteworthy that TTAGGG*-CEDS also has the potential to enhance innate and cellular immunity. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 13 Figure 3. TTAGGG*-CEDS influenced the protein signaling pathways (A) and axes (B) in RAW 264.7 cells. In IP-HPLC, proteins downregulated (blue), upregulated (red), and minimally changed (green) compared to untreated controls. Dominantly suppressed (blue square) and activated (red square) signaling. Telomere- associated proteins (Harmonizome 3.0) were downregulated (●) or upregulated (●) by TTAGGG*-CEDS. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 14 Table 1. Protein expressions in RAW 264.7 cells treated with telomere sequence (TTAGGG)*-CEDS. Signaling pathways Downregulated Proteins Upregulated Proteins Proliferation Ki-67, PCNA, PLK4, CDK4, p15/16, p21, nucleolin p14, CHK1 cMyc/MAX/MAD network MAX, MAD1 Wnt/β-catenin signaling APC, TCF1, Snail Wnt1, β-catenin, AXIN2 p53/Rb/E2F1 signaling p53, Rb1, CDK4, E2F1, E2F4 SHH/PTCH/GLI signaling PTCH1, GLI1 Notch/Jagged signaling Notch1, Jagged2 Epigenetic modification EZH2, PCAF, HMGA2, Ac-lysine KDM4D, MBD4, HMGB1 Protein translation DOHH, eIF5A1, eIF2α eIF2AK3 miRNA biogenesis AGO2, MTDH TRBP2, GW182 Growth factors GH, EGFR, IGF1, TGFα, TGFβ3, Met, FGF1, progesterone GHRH, IGF2R, ALK1, SMAD2/3, SMAD4, SMAD7, HGFα, FGF2, FGF7, ERβ Cytodifferentiation β-actin, calnexin, CRIP1, AP1M1, Ep-CAM, SOSTDC1, tenascin C GAPDH, vimentin, CaM, DLX2, caveolin1 Osteogenesis osteocalcin, aggrecan BMP2, BMP3, BMP4, RUNX2, OPG, RANKL Neuromuscular differentiation myosin-1a, desmin NSEγ, GFAP, NK1R, S100, αSMA RAS signaling NRAS, PI3K, PTEN, PKA1α, AMPKα, PLCβ2, JAK2, PKC, TYK2 HRAS, Rab1, MEKK, p-ERK1, STAT3, AKAP13, p-JNK1, p-PKC1α, SOS1 NFkB signaling SRC1, NFATc1, NFAT5 NFkB, IKK, MDR, GADD45, p38, mTOR p53-mediated apoptosis p53, p63, BAD, APAF1 p73, BAK, PUMA, NOXA, BCL2, c-caspase9, caspase3 FAS-mediated apoptosis FASL FAS, FADD, BID, caspase8, caspase3 PARP-mediated apoptosis PARP1, c-PARP Protection leptin, FOXP4, FOXO1, HSP90, NOS1 HSP27, HO1, FOXO3, NRF2, HSP70, SOD1, GSTO1/2, ALDH1A1 ER stress eIF2α, GADD153, p-GADD153, IRE1α, LC3β HSP27, eIF2AK3, BIP Angiogenesis HIF1α, VEGFR2, endocan, CD106, angiogenin, PDGFA VEGFA, VEGFC, vWF, LYVE1, TEM8, CMG2, enthelin1, FGF2 Survival SP1, sirtuin6 sirtuin1, sirtuin3, sirtuin7 Acute inflammation IL1, IL8, MCP1, CRP TRAF6, MIF Innate immunity CD56, TLR3, α1-antitrypsin Lactoferrin, CAMP, β-defensin1, β-defensin2, TLR2, elafin Cellular immunity CD4, CD34, granzyme B, PD1, CTLA4 CD8, CD20, CD28, CD40, CD44, CD99, perforin Chronic inflammation M-CSF, CD68, CD106, TIMP1, TIMP2, LTA4H, kininogen IL6, IL10, lysozyme, MMP2, cathepsin C, COX1, COX2 Glycolysis LGR4, PPARγ, TIGAR, GLUT1, HK2, LDHA, GAPDH Fibrosis collagen 3A1, FGF1, laminin α5, integrin α5, integrin β1, α1-antitrypsin, tenascin C FGF2, FGF7, uPA, PAI1 Oncogenesis CRK, 14-3-3, MTDH, KLF4, MTA2, CRIP1, HER2, EWSR1, ATR, BMI1, PDCD4, Ets1, TWIST1, BACH1 CEA, AXL, BRCA1, cMyb, ATM, NF1, ZEB1, YAP1, DMBT1, PIM1 Senescence klotho, sirtuin6, p21 sirtuin1, sirtuin3, sirtuin7, caveolin1 Telomere signaling TERT, TRF1, TIN2 The telomere sequence*-CEDS, TTAGGG*-CEDS induced the suppression (blue) and activation (red) of signaling pathways by downregulating (blue) and upregulating (red) the proteins, respectively. The data were compared to the reports of recent manuscripts and Harmonizome 3.0 website. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 15 Canonical E-box sequence*-CEDS induced significant oncogenic signaling in RAW 264.7 cells IP-HPLC results showed that CACGTG*-CEDS upregulated 57proteins (35.8%), downregulated 75 proteins (47.2%), and exhibited minimum effect on 27 proteins (17%) out of 159 cMyc target proteins. In addition, CACGTG*-CEDS concomitantly upregulated 77 proteins (40.3%) and downregulated 58 proteins (30.4%) out of 191 cMyc non-target proteins indirectly. The CACGTG*-CEDS affected the overall protein signaling pathways in RAW 264.7 cells by downregulating cMyc target proteins and reactive proteins as well (Fig. 4A, Table 2), which were summarized as follows according to the expression of cMyc target proteins. Proliferating signaling was partially inactivated by downregulating PCNA (90.6%), PLK4 (82.9%), CDK4 (86.6%). cMyc/MAX/MAD network was suppressed by downregulating cMyc (91.6%), MAX (87.7 %), p27 (91.4%). Wnt/β-catenin signaling appears to be inactivated by downregulating Wnt1 (92.2%), TCF1 (82.4%). P53/Rb/E2F1 signaling was suppressed by downregulating p53 (80.6%), CDK4 (86.6%), E2F1 (91 %). SHH/PTCH/GLI signaling was suppressed by downregulating SHH (89.8%), PTCH1 (90.1%), GLI (83.5 %). Protein translation signaling appears to be inactivated by downregulating DHPS (90.6%). miRNA biogenesis signaling was inactivated by downregulating Drosha (88.4%), MTDH (88.7%) . Growth factor signaling was partially inactivated by downregulating, EGFR (92.2%), Met (89.2%). Cytodifferentiation signaling was partially suppressed by downregulating CRIP1 (83.5%), Ep-CAM (85.9%). ER stress was inactivated by downregulating eIF2AK3 (67%), p-GADD153 (90.6%), IRE1α (90.4%), LC3β (92.9%). Angiogenesis signaling appears to be inactivated by downregulating VEGFR2 (89.9%), endocan (74.8%), CD31 (92%), CD106 (91%), LYVE1 (90.7%), CMG2 (94.1%), angiogenin (77.4%). Survival signaling was suppressed by downregulating SP1 (72.3%), XIAP (91.1%) . Acute inflammation signaling appears to be inactivated by downregulating IL1 (81.4%), CXCR4 (93%). Innate immunity signaling appears to be inactivated by downregulating CD56 (87.3%), TLR2 (77.1%), TLR3 (71.5%), α1-antitrypsin (93.3%). Chronic inflammation signaling was inactivated by downregulating IL12 (85.3%), M-CSF (82.1%), LTA4H (81.9%). (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 16 FAS-mediated apoptosis signaling was suppressed by downregulating FASL (83.6%), FAS (89.3%), FLIP (94.5%), caspase8 (90.3%). Fibrosis signaling was suppressed by downregulating collagen 3A1 (82.9%), integrin α5 (88.4%), integrin β1 (82.7%), PAI1 (94.4%). Senescence signaling appears to be suppressed by downregulating klotho (80.7%), p21 (91.7%), and coincidentally downregulating sirtuin6 (81.9%). Telomere signaling was suppressed by downregulating TERT (87.1%), TRF1 (87.6%), TIN2 (67.6%). Conversely, Notch/Jagged signaling was activated by upregulating Notch1 (105.7%). Osteogenesis signaling was activated by upregulating BMP2 (134.8%), RUNX2 (109.1%), RANKL (113.7%). Neuronal differentiation signaling was activated by upregulating S100 (109.1%), while muscular differentiation signaling was inactivated by downregulating MYH2 (86.1%). RAS signaling appears to be activated by upregulating NRAS (105.5%), pAKT1/2/3 (113.9%), p-STAT3 (110.3%), PKA1α (112.9%), c-Fos (115.3%), JAK2 (113.1%), p-PKCα (119.5%), SOS1 (125.4%). NFkB signaling was activated by upregulating NFkB (123.4%), MDR (125.6%), GADD45 (121%), p38 (117%), SRC1 (108%), mTOR (108.4%). Protection signaling appears to be activated by upregulating FOXO3 (122.4%). Cellular immunity signaling appears to be activated by upregulating CD54 (105.6%) and downregulating PD1 (82.2%). p53-mediated apoptosis signaling was activated by upregulating p73 (121.5%), BAK (105%), PUMA (106.5%), NOXA (107.8%), BAX (114.3%), BCL2 (106%), caspase3 (116.2%). PARP-mediated apoptosis signaling was activated by upregulating PARP1 (110.6%), c-PARP (118.9%). Glycolysis signaling appears to be activated by upregulating HK2 (129.6%), LDHA (109%). In addition, CACGTG*-CEDS, markedly influenced epigenetic modification signaling by downregulating KDM4D (87.2%), EZH2 (91.9%), BRG1 (93.2%), significantly suppressed oncogenesis signaling by downregulating TWIST (94%), BRCA1 (93.3%), PDCD4 (92.9%), MTA2 (90.5%), MTDH (88.7%), ATR (84.9%), HER2 (83.9%), CRIP1 (83.5%), BRCA2 (83.2%), Ets1 (80.9%) . Besides the expressions of cMyc target proteins, the expressions of cMyc non-target proteins in the cells treated with CACGTG*-CEDS were summarized in Table S3. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 17 Consequently, CACGTG*-CEDS strongly impacted the entire protein signaling pathways in RAW 264.7 cells. CACGTG*-CEDS enhanced RAS-NFkB signaling axis, subsequently activating epigenetic modification- protection-Notch/Jagged-osteogenesis signaling axis, p-53 and PARP- mediated apoptosis signaling axis, glycolysis-oncogenesis-chronic inflammation, and cellular immunity signaling axis, while it inactivated proliferation-related signaling axis, ER stress-angiogenesis-survival-senescence-acute inflammation-innate immunity signaling axis, and FAS-mediated apoptosis-fibrosis-telomere signaling axis (Fig. 4B). The results indicate that CACGTG*-CEDS increased the oxidative stress, p53- and PARP-mediated apoptosis, glycolysis, oncogenesis, and chronic inflammation in RAW 264.7 cells, but decreased the proliferation, ER stress, angiogenesis, survival, senescence, acute inflammation, FAS-mediated apoptosis, and telomere instability, thereby, providing oncogenic environment with reduced potential of the cytodifferentiation, regeneration, wound healing, and innate and cellular immunity in the cells. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 18 Figure 4. CACGTG*-CEDS influenced the protein signaling pathways (A) and axes (B) in RAW 264.7 cells. In IP-HPLC, proteins downregulated (blue), upregulated (red), and minimally changed (green) compared to untreated controls. Dominantly suppressed (blue square) and activated (red square) signaling. cMyc target proteins (Harmonizome 3.0) were downregulated (●) or upregulated (●) by CACGTG*-CEDS. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 19 Table 2. Protein expressions in RAW 264.7 cells treated with canonical E-box sequence (CACGTG)*- CEDS. Signaling pathways Downregulated Proteins Upregulated Proteins Proliferation PCNA, PLK4, CDK4, p15/16, p21, p27, CHK1 p14, nucleolin cMyc/MAX/MAD network cMyc, MAX, MAD1, p27 Wnt/β-catenin signaling Wnt1, TCF1 β-catenin, APC, AXIN2 p53/Rb/E2F1 signaling p53, CDK4, E2F1, E2F4 Rb1 SHH/PTCH/GLI signaling SHH, PTCH1, GLI1 Notch/Jagged signaling Notch1, Jagged2 Epigenetic modification histone H1, KDM4D, EZH2, BRG1 MBD4, DNMT1, Ac-lysine, lamin A/C Protein translation DHPS, eIF2AK3 miRNA biogenesis Drosha, Exportin5, MTDH TRBP2 Growth factors EGF, EGFR, TGFα, TGFβ3, SMAD2/3, Met, progesterone GH, IGF1, SMAD4, SMAD7, FGF7, CTGF, ERβ Cytodifferentiation β-actin, TGase2, CRIP1, AP1M1, Ep-CAM, cystatin A, DLX2, VE-cadherin, SOSTDC1, tenascin C α-tubulin, vimentin, FAK, calnexin, claudin1, caveolin1 Osteogenesis PTH/PTHrPR, osteocalcin, aggrecan BMP2, BMP4, osterix, RUNX2, OPG, RANKL, osteopontin, osteonectin Neuromuscular differentiation GFAP, myosin-1a, MYH2, desmin NSEγ, NK1R, S100 RAS signaling PI3K, Rab1, p-ERK1, PTEN, AMPKα, p-TYK2 NRAS, pAKT1/2/3, p-STAT3, PKA1α, PLCβ2, c- Fos, JAK2, p-PKC1α, SOS1 NFkB signaling p-p38, NFATc1, NFAT5 NFkB, MDR, GADD45, p38, SRC1, mTOR p53-mediated apoptosis p53, p63 P73, BAD, BAK, PUMA, NOXA, BAX, BCL2, caspase9, c-caspase9, caspase3 FAS-mediated apoptosis FASL, FAS, FLIP, caspase8 FADD, TRAIL, BID, caspase3 PARP-mediated apoptosis PARP1, c-PARP Protection FOXO1, HSP70, NOS1, HSP90 FOXP4, FOXO3, HSP27, NRF2, HO1, GSTO1/2, SOD1 ER stress eIF2AK3, p-GADD153, IRE1α, LC3β HSP27, BIP, ATF4, ATF6α Angiogenesis VEGFR, endocan, CD31, CD106, LYVE1, CMG2, angiogenin HIF1α, VEGFC, vWF, endothelin1, PDGFA Survival SP1, sirtuin6, XIAP sirtuin3, sirtuin7 Acute inflammation IL1, IL8, CXCR4 TNFα, TRAF6, MCP1, MIF Innate immunity CD56, TLR2, TLR3, α1-antitrypsin Lactoferrin, TLR4, elafin Cellular immunity CD8, CD20, CD34, PD1 CD28, CD40, CD54, IL28, perforin, PDL1 Chronic inflammation IL10, IL12, M-CSF, CD31, CD106, TIMP1, TIMP2, cathepsin K, COX1, LTA4H, kininogen Lysozyme, MMP2, MMP9, MMP10, MMP12, cathepsin C, cathepsin G, COX2 Glycolysis GLUT4, TIGAR HK2, LDHA, GAPDH, GLUT1 Fibrosis collagen 3A1, laminin α5, integrin α5, integrin β1, PAI1, α1-antitrypsin, tenascin C FGF7, CTGF, claudin1 Oncogenesis BMI1, TWIST1, BRCA1, PDCD4, MTA2, MTDH, ATR, HER2, CRIP1, BRCA2, Ets1 XBP1, NF1, ATM, CEA, ZEB1, AXL, EWSR1, cMyb, PIM1, YAP1, KLF4, DMBT1, 14-3-3, CRK Senescence klotho, sirtuin6, p21 sirtuin3, sirtuin7, caveolin1 Telomere signaling TERT, TRF1, TIN2 The canonical E-box sequence*-CEDS, CACGTG*-CEDS induced the suppression (blue) and activation (red) of signaling pathways by downregulating (blue) and upregulating (red) the proteins, respectively. The data were compared to the reports of recent manuscripts and Harmonizome 3.0 website. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 20 Table 3. The targeting efficiency of CEDS using a different DNA motif sequence in RAW 264.7 cells Protein binding site sequence*-CEDS Up-regulation (over 105%) Down- regulation (under 95%) Minimal change (±5%) Total target proteins TTAGGG*-CEDS (telomere repeat sequence) 34 67 6 107 31.6% 62.6% 5.6% 100% CACGTG*-CEDS (canonical E-box sequence) 57 75 27 159 35.8% 47.2% 17% 100% Total 91 142 33 266 34.2% 53.4% 12.4% 100% 12A*-CEDS (nonspecific sequence) 130 122 98 350 37.1% 34.9% 28% 100% (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 21 Nonspecific poly-A 12A*-CEDS induced imbalanced protein signaling in RAW 264.7 cells RAW 264.7 cells were also treated with CEDS using nonspecific poly-A sequence (12A*-CEDS) as a positive control, and analyzed by IP-HPLC to compared with the results of TTAGGG*-CEDS and CACGTG*- CEDS. In constrast, 12A*-CEDS resulted in imbalanced protein signaling in RAW 264.7 cells, activating epigenetic methylation, oncogenesis, and telomere instability, leading to chronic inflammation and apoptosis, in the absence of cellular growth and differentiation, wound healing, and ROS protection (Fig. 5, Table 4) . The variable protein expressions after 12A*-CEDS were detected by IP-HPLC using 350 antisera, and their imbalaced influences in different signaling pathways were summarized and described in Supplement Text. Therefore, it is postulated that 12A*-CEDS induced irregular upregulation and downregulation of multiple signaling pathways due to imbalanced stimulation of gene transcription by targeting poly-A sequences widely distributed in genome, resulted in the aging and retrogressive changes with a high potential of oncogenesis. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 22 Figure 5. The telomere sequence (TTAGGG)*-CEDS influenced the protein signaling pathway system (A) and axes (B) in RAW 264.7 cells. The IP-HPLC results revealed proteins that were downregulated ( blue), upregulated (red), and minimally changed (green) compared to the untreated controls. Dominantly suppressed (blue square) and activated (red square) signaling pathways. Telomere-associated proteins (Harmonizome 3.0), downregulated (●) or upregulated (●) by the TTAGGG*-CEDS. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 23 Table 4. Protein expressions in RAW 264.7 cells treated with telomere sequence (TTAGGG)*-CEDS. Signaling pathways Downregulated Proteins Upregulated Proteins Proliferation Ki-67, PCNA, PLK4, CDK4, p15/16, p21, nucleolin p14, CHK1 cMyc/MAX/MAD network MAX, MAD1 Wnt/β-catenin signaling APC, TCF1, Snail Wnt1, β-catenin, AXIN2 p53/Rb/E2F1 signaling p53, Rb1, CDK4, E2F1, E2F4 SHH/PTCH/GLI signaling PTCH1, GLI1 Notch/Jagged signaling Notch1, Jagged2 Epigenetic modification EZH2, PCAF, HMGA2, Ac-lysine KDM4D, MBD4, HMGB1 Protein translation DOHH, eIF5A1, eIF2α eIF2AK3 miRNA biogenesis AGO2, MTDH TRBP2, GW182 Growth factors GH, EGFR, IGF1, TGFα, TGFβ3, Met, FGF1, progesterone GHRH, IGF2R, ALK1, SMAD2/3, SMAD4, SMAD7, HGFα, FGF2, FGF7, ERβ Cytodifferentiation β-actin, calnexin, CRIP1, AP1M1, Ep-CAM, SOSTDC1, tenascin C GAPDH, vimentin, CaM, DLX2, caveolin1 Osteogenesis osteocalcin, aggrecan BMP2, BMP3, BMP4, RUNX2, OPG, RANKL Neuromuscular differentiation myosin-1a, desmin NSEγ, GFAP, NK1R, S100, αSMA RAS signaling NRAS, PI3K, PTEN, PKA1α, AMPKα, PLCβ2, JAK2, PKC, TYK2 HRAS, Rab1, MEKK, p-ERK1, STAT3, AKAP13, p-JNK1, p-PKC1α, SOS1 NFkB signaling SRC1, NFATc1, NFAT5 NFkB, IKK, MDR, GADD45, p38, mTOR p53-mediated apoptosis p53, p63, BAD, APAF1 p73, BAK, PUMA, NOXA, BCL2, c-caspase9, caspase3 FAS-mediated apoptosis FASL FAS, FADD, BID, caspase8, caspase3 PARP-mediated apoptosis PARP1, c-PARP Protection leptin, FOXP4, FOXO1, HSP90, NOS1 HSP27, HO1, FOXO3, NRF2, HSP70, SOD1, GSTO1/2, ALDH1A1 ER stress eIF2α, GADD153, p-GADD153, IRE1α, LC3β HSP27, eIF2AK3, BIP Angiogenesis HIF1α, VEGFR2, endocan, CD106, angiogenin, PDGFA VEGFA, VEGFC, vWF, LYVE1, TEM8, CMG2, enthelin1, FGF2 Survival SP1, sirtuin6 sirtuin1, sirtuin3, sirtuin7 Acute inflammation IL1, IL8, MCP1, CRP TRAF6, MIF Innate immunity CD56, TLR3, α1-antitrypsin Lactoferrin, CAMP, β-defensin1, β-defensin2, TLR2, elafin Cellular immunity CD4, CD34, granzyme B, PD1, CTLA4 CD8, CD20, CD28, CD40, CD44, CD99, perforin Chronic inflammation M-CSF, CD68, CD106, TIMP1, TIMP2, LTA4H, kininogen IL6, IL10, lysozyme, MMP2, cathepsin C, COX1, COX2 Glycolysis LGR4, PPARγ, TIGAR, GLUT1, HK2, LDHA, GAPDH Fibrosis collagen 3A1, FGF1, laminin α5, integrin α5, integrin β1, α1-antitrypsin, tenascin C FGF2, FGF7, uPA, PAI1 Oncogenesis CRK, 14-3-3, MTDH, KLF4, MTA2, CRIP1, HER2, EWSR1, ATR, BMI1, PDCD4, Ets1, TWIST1, BACH1 CEA, AXL, BRCA1, cMyb, ATM, NF1, ZEB1, YAP1, DMBT1, PIM1 Senescence klotho, sirtuin6, p21 sirtuin1, sirtuin3, sirtuin7, caveolin1 Telomere signaling TERT, TRF1, TIN2 The telomere sequence*-CEDS, TTAGGG*-CEDS induced the suppression (blue) and activation (red) of signaling pathways by downregulating (blue) and upregulating (red) the proteins, respectively. The data were compared to the reports of recent manuscripts and Harmonizome 3.0 website. (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 24

This study demonstrated the CEDS targeting a six bps telomere repeat sequence and a six bps palindromic canonical E-box sequence in RAW 264.7 cells. Both sequences are favorable as a CEDS target due to their abundant distribution throughout the genome and their important roles in gene transcription and regulation ( 4, 18). As a result, TTAGGG*-CEDS inactivated telomere signaling, RAS-proliferation-growth-cytodifferentiation signaling axis, while enhancing NFkB-ROS-inflammation signaling axis, p53- and FAS-mediated apoptosis signaling with concomitant inactivation of ER stress-survival-senescence signaling axis, resulting in extensive cell death as seen in the cytological observation. However, it was found that TTAGGG*-CEDS upregulated 34 proteins (31.6%), downregulated 67 proteins (62.6%), and had minimal effect on 6 proteins (5.6%) out of 107 telomere-associated proteins observed in this study. Since TTAGGG*-CEDS tended to downregulate rather than upregulate the telomere-associated proteins, it is postulated that TTAGGG*-CEDS stabilizes the telomere sequences, thereby, inactivates the telomere- associated proteins and subsequently attenuates the signaling relevant to telomere instability in cells. In contrast, CACGTG*-CEDS activated RAS-NFkB signaling axis and subsequently enhanced ROS- p53 and PARP-associated apoptosis signaling, glycolysis-oncogenesis-chronic inflammation axis, while inactivated proliferation-growth axis, ER stress-angiogenesis-survival-senescence axis, resulting in the increased oncogenic potential and delayed regeneration and wound healing. However, CACGTG*-CEDS upregulated 57 proteins (35.8%), downregulated 75 proteins (47.2%), and showed minimal effect on 27 proteins (17%) out of 159 cMyc target proteins, indicating relatively even upregulation (35.8%) and downregulation (47.2%) of cMyc target proteins compared to TTAGGG*-CEDS. Therefore, it is postulated that CACGTG*-CEDS affects palindromic six bps dsDNA, canonical dsCACGTG consisting of three Pyu dsDNA segments, by activating forward and reverse direction, leading to dual protein binding and sliding on the canonical E-box site. This may result in the selective upregulation and downregulation of cMyc target proteins depending on the context of molecular interaction, such as cMyc-MAX- MAD network. Consequently, TTAGGG*-CEDS induced potent anticancer effect on RAW 264.7 cells by stabilizing the telomere sequence, which functions as a protective role for chromosome, while CACGTG*-CEDS induced (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 25 significant oncogenic effect on the cells by activating the major oncogene, c-Myc. Therefore, it is suggested that CEDS can properly target DNA motifs such as telomere repeat sequence and canonical E-box sequence in the genomic DNA of RAW 264.7 cells, and upon further investigation, the TTAGGG*-CEDS and CACGTG*- CEDS will be useful candidate tools to regulate a specific protein signaling axis in cells. Taken together, this series of study found that CEDS can target DNAs and RNAs distributed in vitro and in vivo environment in a sequence-specific manner. However, the CEDS-induced modulation of the target gene remains to be elucidated by further precise molecular genetic investigation. Acknowledgments We would like to express our gratitude to the late Professor Je Geun Chi and the late Dr. Soo Il Chung, who contributed to this research in part.

1. S. K. Lee, D. G. Lee, Y. S. Kim, Development of Hydrogen Bonding Magnetic Reaction-based Gene Regulation through Cyclic Electromagnetic DNA Simulation in Double-Stranded DNA. arXiv:1210.7091, (2024); published online EpubJun 29 (10.48550/arXiv.1210.7091). 2. L. M. Carson, R. L. Flynn, Highlighting vulnerabilities in the alternative lengthening of telomeres pathway. Current opinion in pharmacology 70 , 102380 (2023); published online EpubJun (10.1016/j.coph.2023.102380). 3. V. Gubala, J. E. Betancourt, J. M. Rivera, Expanding the Hoogsteen edge of 2'-deoxyguanosine: consequences for G-quadruplex formation. Organic letters 6, 4735-4738 (2004); published online EpubDec 9 (10.1021/ol048013v). (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 26 4. C. Grandori, J. Mac, F. Siebelt, D. E. Ayer, R. N. Eisenman, Myc- Max heterodimers activate a DEAD box gene and interact with multiple E box-related sites in vivo. The EMBO journal 15, 4344-4357 (1996); published online EpubAug 15 ( 5. M. H. Seo, D. W. Kim, Y. S. Kim, S. K. Lee, Pentoxifylline-induced protein expression change in RAW 264.7 cells as determined by immunoprecipitation-based high performance liquid chromatography. PloS one 17, e0261797 (2022)10.1371/journal.pone.0261797). 6. C. S. Yoon, M. K. Kim, Y. S. Kim, S. K. Lee, In vitro protein expression changes in RAW 264.7 cells and HUVECs treated with dialyzed coffee extract by immunoprecipitation high performance liquid chromatography. Scientific reports 8, 13841 (2018); published online EpubSep 14 (10.1038/s41598- 018 -32014-z). 7. B. Taciak, M. Bialasek, A. Braniewska, Z. Sas, P. Sawicka, L. Kiraga, T. Rygiel, M. Krol, Evaluation of phenotypic and functional stability of RAW 264.7 cell line through serial passages. PloS one 13, e0198943 (2018)10.1371/journal.pone.0198943). 8. M. K. Kim, S. G. Kim, S. K. Lee, 4-Hexylresorcinol-in duced angiogenesis potential in human endothelial cells. Maxillofacial plastic and reconstructive surgery 42, 23 (2020); published online EpubDec (10.1186/s40902-020-00267-2). 9. M. K. Kim, C. S. Yoon, S. G. Kim, Y. W. Park, S. S. Lee, S. K. Lee, Effects of 4-Hexylresorcinol on Protein Expressions in RAW 264.7 Cells as Determined by Immunoprecipitation High Performance Liquid Chromatography. Scientific reports 9, 3379 (2019); published online EpubMar 4 (10.1038/s41598-019-38946-4). 10. S. M. Kim, M. Y. Eo, Y. J. Cho, Y. S. Kim, S. K. Lee, Immunoprecipitation high performance liquid chromatographic analysis of healing process in chronic suppurative osteomyelitis of the jaw. Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo- Facial Surgery 46, 119-127 (2018); published online EpubJan (10.1016/j.jcms.2017.10.017). 11. S. M. Kim, M. Y. Eo, Y. J. Cho, Y. S. Kim, S. K. Lee, Wound healing protein profiles in the postoperative exudate of bisphosphonate-related osteonecrosis of mandible. European archives of oto- rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies 274, 3485-3495 (2017); published online EpubSep (10.1007/s00405-017-4657-x). (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint 27 12. S. M. Kim, M. Y. Eo, Y. J. Cho, Y. S. Kim, S. K. Lee, Differential protein expression in the secretory fluids of maxillary sinusitis and maxillary retention cyst. European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies 274, 215-222 (2017); published online EpubJan (10.1007/s00405-016-4167-2). 13. S. M. Kim, D. Jeong, M. K. Kim, S. S. Lee, S. K. Lee, Two different protein expression profiles of oral squamous cell carcinoma analyzed by immunoprecipitation high-performance liquid chromatography. World journal of surgical oncology 15, 151 (2017); published online EpubAug 8 (10.1186/s12957-017- 1213-5). 14. I. S. Lee, D. W. Kim, J. H. Oh, S. K. Lee, J. Y. Choi, S. G. Kim, T. W. Kim, Effects of 4- Hexylresorcinol on Craniofacial Growth in Rats. International journal of molecular sciences 22, (2021); published online EpubAug 19 (10.3390/ijms22168935). 15. S. S. Lee, S. M. Kim, Y. S. Kim, S. K. Lee, Extensive protein expression changes induced by pamidronate in RAW 264.7 cells as determined by IP-HPLC. PeerJ 8, e9202 (2020)10.7717/peerj.9202). 16. C. S. Yoon, M. K. Kim, Y. S. Kim, S. K. Lee, In vivo protein expression changes in mouse livers treated with dialyzed coffee extract as determined by IP-HPLC. Maxillofacial plastic and reconstructive surgery 40, 44 (2018); published online EpubDec (10.1186/s40902-018-0183-z). 17. J. H. Yoon, D. W. Kim, S. K. Lee, S. G. Kim, Effects of 4-hexylresorcinol administration on the submandibular glands in a growing rat model. Head & face medicine 18, 16 (2022); published online EpubJun 6 (10.1186/s13005-022-00320-7). 18. P. Vogt, Potential genetic functions of tandem repeated DNA sequence blocks in the human genome are based on a highly conserved "chromatin folding code". Human genetics 84, 301-336 (1990); published online EpubMar (10.1007/BF00196228). (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. The copyright holder for this preprintthis version posted August 27, 2024. ; https://doi.org/10.1101/2024.08.25.609549doi: bioRxiv preprint