Inactivation of the Hippo pathway promotes Yap nuclear translocation, enabling execution of a transcriptional program that induces tissue growth. Genetic lesions of Hippo intermediates only identify a minority of cancers with illegitimate YAP activation. Yap has been implicated in resistance to targeted therapies, but the mechanisms by which YAP may impact adaptive resistance to MAPK inhibitors are unknown.S127A, alone or in combination with endogenous expression of either HrasG12V or BrafV600E. We also generated cell lines expressing dox-inducible sh-miR-E-YAP and/or YAPS127A. We used cell viability, invasion assays, immunofluorescence, Western blotting, qRT-PCRs, flow cytometry and cell sorting, high-throughput bulk RNA sequencing and in vivo tumorigenesis to investigate YAP dependency and response of BRAF-mutant cells to vemurafenib.We screened 52 thyroid cancer cell lines for illegitimate nuclear YAP localization by immunofluorescence and fractionation of cell lysates. We engineered a doxycycline (dox)-inducible thyroid-specific mouse model expressing constitutively nuclear YAPWe found that 27/52 thyroid cancer cell lines had constitutively aberrant YAP nuclear localization when cultured at high density (NU-YAP), which rendered them dependent on YAP for viability, invasiveness and sensitivity to the YAP-TEAD complex inhibitor verteporfin, whereas cells with confluency-driven nuclear exclusion of YAP (CYT-YAP) were not. Treatment of BRAF-mutant thyroid cancer cells with RAF kinase inhibitors resulted in YAP nuclear translocation and activation of its transcriptional output. Resistance to vemurafenib in BRAF-mutant thyroid cells was driven by YAP-dependent NRG1, HER2 and HER3 activation across all isogenic human and mouse thyroid cell lines tested, which was abrogated by silencing YAP and relieved by pan-HER kinase inhibitors. YAP activation induced analogous changes in BRAF melanoma, but not colorectal cells.V600E-mutant cells encompassing effectors in the NRG1 signaling pathway, which play a central role in the insensitivity to MAPK inhibitors in a lineage-dependent manner. HIPPO pathway inactivation serves as a lineage-dependent rheostat controlling the magnitude of the adaptive relief of feedback responses to MAPK inhibitors in BRAF-V600E cancers.YAP activation in thyroid cancer generates a dependency on this transcription factor. YAP governs adaptive resistance to RAF kinase inhibitors and induces a gene expression program in BRAFThe online version contains supplementary material available at 10.1186/s12943-022-01676-9. V600E-driven cancers, cell autonomous intrinsic resistance to RAF kinase inhibitors in melanomas, colorectal or thyroid tumors is commonly due to distinct lineage-dependent mechanisms that ultimately converge on reactivation of ERK [Complete responses to targeted therapies for most cancer types remain elusive due to development of primary or acquired resistance. In the context of BRAFn of ERK –6.V600E-mutant lung cancer cell line. YAP knockdown also overcame resistance to RAF and MEK inhibitors in other cell types driven by mutant BRAF or RAS [Illegitimate activation of YAP, a transcriptional coactivator that upon translocation to the nucleus executes the gene expression program of the Hippo pathway, has been identified as an underlying factor driving resistance to genetic or small molecule MAPK pathway inhibitors. A genome-wide CRISPR-Cas9 screen identified NF2, a canonical upstream regulator of the Hippo pathway, as a top hit driving resistance to vemurafenib in melanoma cells . SimilarF or RAS . Two indF or RAS . MoreoveF or RAS –13.The Hippo pathway is an evolutionarily conserved kinase cascade that controls multiple biological processes during development and tissue regeneration, most prominently cell growth and organ size . The canPhysiological control of cytoplasmic-nuclear shuffling of YAP is subject to multiple inputs . Cell coOverexpression or inappropriate activation of YAP or TAZ promote tumorigenesis in mouse models and likely play a pivotal role in many human cancers. However, mutations of canonical effectors in the HIPPO pathway are rare in cancer , 24. DesV600E melanoma cell lines induces actin cytoskeletal remodeling, which increases YAP/TAZ nuclear localization and promotes drug resistance and cancer cell viability [BrafV600E context, constitutively nuclear YAPS127A expression induces larger tumors and decreases survival. Intrinsic resistance to vemurafenib in BRAF-mutant thyroid cancer cell lines has been shown to be due to attenuation of the negative feedback by vemurafenib on the NRG1-HER3/HER2 pathway, with the consequent reactivation of ERK [The mechanisms accounting for YAP-induced resistance to small molecule inhibitors of the RAS-MAPK signaling pathway remain unclear. Prolonged vemurafenib treatment in BRAFiability . YAP caniability , 34. HowIntriguingly, vemurafenib treatment of BRAF-mutant thyroid cancer cell lines induced translocation of Yap to the nucleus and activation of its transcriptional output, which included key effectors in the NRG1 signaling pathway. Intrinsic resistance to vemurafenib was dampened by genetic or pharmacological targeting of Yap and by HER kinase inhibitors. These data implicate Yap as a central orchestrator of primary resistance to RAF kinase inhibition in BRAF mutant thyroid cancer. The Yap transcriptional output encompasses other MAPK effectors, including the three RAS genes , suggestThe origin of the mice and the generation of the animal models is described in 2. Thyroid tumors were imaged using Vevo-770 High-Resolution In Vivo Micro-Imaging System . Volume was calculated by manually tracing the margin of the tumor every 250 μm using the instrument software.Mice were anesthetized with isoflurane with 1%OResected mouse thyroid and metastases tissues were fixed in 4% paraformaldehyde (PFA), paraffin-embedded and sectioned into 4 μm sections. H&E-stained sections were evaluated by thyroid pathologists blinded to the mouse genotype. The sections were deparaffinized and immunostained with specific antibodies  as described previously .Tumors were collected and disaggregated as previously described . KATE-poCells were cultured in 150 mm plates and upon reaching confluency, washed with PBS and incubated with 4%PFA for 15 minutes with gentle agitation. Adherent cells were scraped, collected in a 15 ml tube and centrifuged for 5 minutes at 1000 rpm at 4 °C. The cell pellet was resuspended in 4% PFA, transferred to a 15 ml tube with 2% agarose mold, centrifuged for 2 minutes at 1000 rpm, and kept at 4 °C overnight. The cell pellet was washed with 70% methanol, paraffin-embedded and processed at the Molecular Cytology Facility at MSKCC. The CMA consisted of two cores for each cell line. TMAs consisting of 41 human PTCs, 67 PDTCs and 16 ATCs were obtained from the Pathology Department at MSKCC. A subset of the PTCs and all PDTCs and ATCs were previously genotyped by MSK-IMPACT NGS.Cells were plated onto 24-well plates containing 12 mm glass coverslips. To screen for YAP subcellular localization cells were incubated with 10%FBS at high and low cell density or in 1%FBS for 2 days. For expression of YAP mutants or YAP shRNAs cells were incubated for 3 days in medium with/without dox in 1%FBS. Cells were then washed once with ice-cold PBS and fixed in cold methanol for 15 minutes followed by 15 minutes with 1.6%PFA. Cells were permeabilizated with 0.1%Triton X-100 for 5 minutes, blocked with 5%BSA for 15 minutes and incubated with YAP antibody (1:100) overnight at 4C. The cells were then incubated for 1 h with secondary antibody (1:500) and DAPI (1:100) (ThermoFisher#62248) and imaged using a confocal microscope.S127A and YAPS94A cDNAs were subcloned from pQCXIH-Flag-YAP-S127A (Addgene#33092) and pQCXIH-Myc-YAP-S94A (Addgene#33094), respectively, into the pLVX-Tight-Puro vector (Clontech) with NotI-EcoRI. Cancer cell lines were transduced with lentiviral particles containing pLVX-Tight-Puro-vector with YAPS127A or YAPS94A and with pLVX-Tet-On Advanced vector (Clontech). For YAP knockdown, miR-E-shRNA sequences were cloned into lentiviral Tet-ON all-in-one LT3GEPIR as described [YAPescribed . All conFor growth assays 20,000 cells/well were plated into 24-well plates for 24 h. Cells were treated with/without doxycycline in media containing 1%FBS for the indicated times, collected by trypsinization, and viable cells counted using Vi-CELL-XR (Beckman Coulter). For crystal violet assays the cells were pre-treated with doxycycline for 2 days and then plated onto 48-well plates (3000cells/well). After 24 h, cells were treated with vehicle or the indicated concentration of drugs in media containing 1%FBS with/ without dox for 72 h. Cells were washed 1xPBS, fixed with 4%PFA for 10 minutes, stained with 0.1% crystal violet and washed thrice by immersing in water. After drying 10% acetic acid was added and incubated for 10 minutes in a shaker. Absorbance was measured in a 96-well plate at 590 nm.Cells were seeded onto 6-well plates and after confluency wounds were generated using a sterile 1 mL micropipette tip in triplicate for each condition, PBS-washed and incubated with 10%FBS or 1%FBS media containing vehicle (DMSO) or dox. The gap was imaged at 0 and 24 h using an inverted microscope. Gap areas were calculated by ImageJ.Total RNA was isolated using TRIzol (Invitrogen#15596018). Equal amounts of RNA 2 μg) were subjected to DNA digestion  and subsequently reverse transcribed into cDNA using SuperScript® III First-Strand Synthesis SuperMix (Invitrogen#18080400). Quantitative PCR was then performed using gene-specific primer sets  supplemented with proteinase/phosphatase inhibitors (Roche). Subcellular fractions were obtained using NE-PER Nuclear and Cytoplasmic Extraction Reagents (ThermoFisher Scientific#78835). Protein concentration was determined using the Pierce-BCA kit (ThermoFisher Scientific#23225) on a microplate reader (SpectraMax M5). For western blotting, 20 μg proteins were size-separated in 4-12% Bis-Tris SDS-PAGE gels (Invitrogen#NP0336BOX), transferred to PVDF membranes and immunoblotted after blocking with 5% skim-milk with corresponding antibodies in 5%BSA (Sigma#A7906) or 5% nonfat milk. Bound antibodies were detected by chemiluminescence using the ECL detection system . Antibodies are listed in +Kate using BD FACS Aria. Approximately 20,000 +Kate cells were collected into TRIzolLS (Invitrogen#10296010) and RNA isolated. One thyroid tumor per mouse was used for each biological replicate. After RiboGreen quantification and quality control by Agilent BioAnalyzer, 1.4-2 ng total RNA with RNA integrity numbers ranging from 8.2 to 9.8 underwent amplification using the SMART-Seq v4 Ultra Low Input RNA Kit (Clonetech#63488), with 12 cycles of amplification. Subsequently, 10 ng of amplified cDNA was used to prepare libraries with the KAPA Hyper Prep Kit (Kapa Biosystems KK8504) using 8 cycles of PCR. Samples were barcoded and run on a HiSeq-4000 in a PE50 run, using the HiSeq 3000/4000 SBS Kit (Illumina). An average of 39 million paired reads were generated per sample and the percent of mRNA bases per sample ranged from 77 to 82%.Tumors were dissected and placed in ice-cold digestion media  and minced. The disaggregated tissue was collected in digestion media and incubated at 37C for 1 h, vortexing every 15 min. Cells were passed through a 70 μM filter to remove tissue debris and the single cell suspension washed with PBS. Cells were resuspended in FACS buffer  and sorted for Frozen cells were lysed in 1 mL TRIzol, and RNA extracted using the miRNeasy Micro Kit (Qiagen#217084) on the QIAcube Connect (Qiagen) with 350 μL input. Samples were eluted in 15 μL RNase-free water. After RiboGreen quantification and quality control by Agilent BioAnalyzer, 500 ng of total RNA with RIN values of 9.5-10 underwent polyA selection and TruSeq library preparation (TruSeq Stranded mRNA LT Kit#RS-122-2102), with 8 cycles of PCR. Samples were barcoded and run on a NovaSeq-6000 in a PE50 run, using the NovaSeq 6000-SP Reagent Kit (100 Cycles) (Illumina). An average of 27 million paired reads was generated per sample. Ribosomal reads represented 1.1-2.4% of the total and the percent of mRNA bases averaged 72%.www.partek.com). In brief, raw reads were aligned to mouse assembly mm10 or human assembly hg38 with STAR aligner using default parameters. The aligned reads were quantified to annotation model (Partek E/M) using mm10 Ensembl release 95 or hg38 Ensembl Release 91.v2 and normalized using Transcripts Per Million and addition of 0.0001 to generate a normalized non-zero expression count matrix.RNA-seq analysis was performed using Partek_Flow  derived from mouse thyroid cancers were cultured in the presence of dox to induce YAPS127A, resuspended in 50% Matrigel (Corning) and implanted (5 × 106 cells/mice) into the flank of 8 to 10-week-old female nude mice (TACONIC Biosciences). Mice were fed dox-impregnated chow to maintain YAPS127A expression in the implanted cells. Treatments were initiated after tumors were established, with a tumor volume of ~200mm3 as estimated by caliper measurements (width2×length× 0.52). Mice were weighed at the start and twice a week during the treatment period, tumor volume was measured every 2–3 days. Mice were humanely euthanized and the dissected tumors flash-frozen in liquid N2 or fixed in 4%PFA. For Fig. S127A) were implanted 1 week apart from each other and all mice fed with dox-impregnated chow for 2 weeks to allow tumors to engraft. The dox-chow was substituted with normal chow in group 1 (OFF-DOX) for 1 week. At this point, both groups (OFF-DOX and ON-DOX) had a similar tumor volume (200mm3), at which time each group was randomly assigned for treatment with vehicle or PLX4720  was used. Graphs represent Ẋ ± SD or SEM. Similar variance between groups was tested by F-Test; if different, Welch’s correction was applied. NF2 are the most prevalent , leading to an increase in the MAPK signaling output [HrasG12V/Nf2flox2 mice. For this we crossed the TPO-Cre/FR-HrasG12V/Nf2flox2 mice with mice harboring homozygous alleles with flox sites bracketing Yap exons 1 and 2 (TPO-Cre/FR-HrasG12V/Nf2flox2/Yapflox2) , 4.3% of poorly differentiated (PDTC) and anaplastic cancers (ATC) and 18% of thyroid cancer cell lines , 43. Amog output . As a coS127A, alone or in combination with endogenous expression of either HrasG12V or BrafV600E in thyroid cells   than cells with other or unknown driver mutations (36%)  Fig. B right. YAP Fig. C. In sumS127A mutant (YAPS127A-FLAG). Three-day exposure to dox in sh-mirE-YAP-transduced lines silenced YAP expression, whereas dox-induced expression of FLAG-tagged YAP for 3 days in CYT-YAP cell lines promoted its nuclear localization . Cells were cultured with dox to maintain expression of YAPS127A. Silencing of YAPS127A by 6 days of dox withdrawal reduced cell viability in all the mouse cell lines  or inhibiting YAP transactivation with verteporfin for 4 weeks decreased tumor size in YAPS127A mice   Fig. H. In sumYAP activation has been implicated in resistance to MAPK pathway inhibitors in other cancer lineages. We investigated whether treatment with selective RAF or MEK inhibitors altered YAP cytoplasmic-nuclear shuttling and YAP transcriptional output. Treatment of the indicated CYT-YAP cell lines with vemurafenib re-localized YAP to the nucleus within 24-48 h, as shown by immunofluorescence and Western blots of nuclear and cytoplasmic lysates  and ERBB signalling (#10)  vary between BRAFelanomas –51. In telanomas . Analysitor Fig. E. YAP siHER3 (ERBB3), HER2 (ERBB2) and NRG1 mRNA levels. Silencing YAP reduced the expression of these genes in nuclear YAP cell lines, whereas in cytoplasmic YAP cell lines, expression of YAPS127A increased them  is associated with an increase of HER3 and HER2 in the cytoplasm, which is blocked with verteporfin, indicating that YAP1 activation governs this process Fig. F. Taken S127A expression rendered CYT-YAP cell lines comparatively resistant to the combination , which when applied to other contexts predict for YAP1-TEAD dependency [The pivotal role of YAP on the transcriptional regulation of genes involved in growth control, coupled to the diversity of inputs that regulate its cytoplasmic-nuclear shuttling, renders this pathway particularly vulnerable to disruptions in cancer . Howeverpendency .OFF) primarily corresponded to neuroendocrine-like tumors, such as retinoblastoma, small cell lung cancer and neuroendocrine prostate cancer. In these lineages, the YAP-TEAD complex functions as a tumor suppressor. This is not the case in the CYT-YAP thyroid cancer cell lines described here, since enforced YAPS127A expression consistently induced cell growth.Disruption of the activation of Hippo signaling by cell contact has been used as an approach to identify non-canonical pathways that promote YAP nuclear translocation , 21. We Although YAP-TEAD activation can promote resistance to a diverse set of cancer therapies, it has been dominantly implicated in driving insensitivity or acquired resistance to inhibition of drivers of the MAPK pathway. Interestingly, YAP activation signatures consistently overlap with MAPK and KRAS transcriptional outputs . In variV600E-driven thyroid cancers in vivo. The NRG1 pathway has been implicated in thyroid cancer pathogenesis at many levels. Genome-wide association studies identified a SNP within intron 1 of the NRG1 gene to be strongly associated with thyroid cancer (p < 10− 9) in European populations [The NRG1 pathway was the top IPA gene expression signature induced by Yap in Brafulations . This waulations . Moreoveulations .S127A, or conversely, of YAP targeted shRNAs, represent the opposite activation states of the YAP pathway. Since canonical HIPPO pathway mutations are infrequent in thyroid cancer, it is likely that in most tumors YAP pathway activity lies somewhere in between these extremes. Thus YAP/TEAD activity may serve as a rheostat controlling the magnitude of adaptive changes in RTK signaling following MAPK inhibition  Top: HIPPO pathway alterations in thyroid cancer cell lines derived from papillary thyroid carcinomas (PTC) or poorly differentiated or anaplastic thyroid cancers (PDTC/ATC). Bottom: Oncoprint of HIPPO pathway alterations in thyroid cancer cell lines, and in PTC, PDTC or ATC tissues. MUT: mutations; AMP: amplification; HOM del: homozygous deletion. B) Schematic design of transgenic lines used to investigate the role of Yap in transformation by HrasG12V in the context of Nf2 loss. C) IHC of Yap1 in thyroid sections of the indicated genotypes. D) Thyroid tumor volume by ultrasound at 10 and 20 weeks showing effects of Yap inactivation on tumor development in HrasG12V/Nf2flox mice. **p < 0.01; ***p < 0.001. Fig Sup 2. YAP Western blots of nuclear (N) and cytoplasmic (C) fractions of confluent cells. TATA-BS: nuclear fraction control. HK1: cytoplasmic fraction control. All cell lines were grown to > 90% confluency in 10% FBS. Two top panels: NU-YAP cell lines; Two lower panels: CYT-YAP cell lines. Fig Sup 3. A) Immunofluorescence for YAP, FLAG and DAPI in NUC-YAP and CYT-YAP cell lines in 1%FBS following 3 days of dox-induced expression of shYAP or YAPS127A, respectively. B) Western blots probed against the indicated antibodies. Cells treated with dox for 3 days in 1%FBS. C) Cell viability after expression of FLAG-YAPS94A in NUC-YAP and CYT-YAP cell lines. D) Representative images of mechanical scratch assays at baseline and 24 h after the lesion in NUC-YAP (red) and CYT-YAP (blue) cell lines. E) Top: Representative images of 24 h mechanical scratch assays in NUC-YAP and CYT-YAP with or without dox-inducible expression of YAP shRNA. Bottom: Quantification of effects of YAP shRNA on wound healing in NU-YAP and CYT-YAP lines. F) Top: Wound healing in CYT-YAP cell lines with or without dox-induced expression of YAPS127A. Bottom: quantification of effects of expression of YAPS127A on wound healing in CYT-YAP lines. Data in panels C, E and F represent 3 independent experiments with each line and condition. *p < 0.05 **p < 0.01 ***p < 0.001. Fig Sup 4. A) GSEA of RNA-seq of tumor cells sorted from YAPS127A-driven mouse thyroid tumors revealed a significant increase in the Cordenonsi_YAP_conserved gene expression signature compared with thyroid cells from WT mice. B) NES and Nom p-values for each YAP signature from the GSEA of RNA-seq of the indicated human thyroid cancer cell comparators  comparing NU-YAP vs CYT-YAP and CYT-YAP vs CYT-YAPS127A. Statistically significant (p < 0.05) up and downregulated genes are represented in light red and light blue, respectively, and YAP-Cluster 2 signature genes common to both groups are highlighted in the respective dark colors. There is an inverse relationship in expression of YAP-Cluster 2 genes in the two comparators: upregulated in NU-YAP vs CYT-YAP and downregulated in CYT-YAP vs CYT-YAPS127A. Fig Sup 5. Time course of vemurafenib (1000 nM) on expression and phosphorylation of the indicated proteins in NU-YAP cell lines (Hth104 and SW1736) after YAP silencing and CYT-YAP cell lines (MDAT32 and BHT101) after expression of YAPS127A in 10% FBS. Fig Sup 6. A) Baseline mRNA expression by real-time qRT-PCR of ERBB3 and ERBB2 in NU-YAP cell lines compared with CYT-YAP cell lines. B) Effect of dox-withdrawal on Erbb3 and Erbb2 mRNAs in Braf-YAPS127A mouse cell line (BY96s). C) ERBB3 and ERBB2 mRNA fold-change after vemurafenib relative to vehicle in NU-YAP vs CYT-YAP cell lines. D) Western blot showing the expression of the indicated proteins after a 48 h treatment with 1 μM vemurafenib and after silencing of ERBB2 or ERBB3 in a representative NU-YAP (8505C) cell line. The vertical lines represent the sites of a deleted lane. **p < 0.01 ***p < 0.001. Fig Sup 7. A) YAP immunofluorescence in Braf.pV600E-mutant melanoma (SK-MEL28 and MM96L) and colorectal  cancer cell lines in sparse and confluent conditions in the presence of 10% FBS. B) Cell viability after dox-induced expression of shYAP or FLAG-YAPS127A in CYT-YAP melanoma and colorectal lines for 6d. C) Dose-dependent effects of a 6-day incubation with vemurafenib on cell viability of CYT-YAP cells with or without dox-induced expression of YAPS127A. D) Effect of YAPS127A on ERBB3 and ERBB2 mRNA after 24 h of vemurafenib treatment in melanoma cell lines. E) Time course of vemurafenib (1000 nM) on expression and phosphorylation of HER2 and HER3 in SK-MEL28 cells in the presence or absence of YAPS127A in 10% FBS. F) Effect of dox-induced expression of YAPS127A in SK-MEL-28 cells by vemurafenib, lapatinib or their combination. Growth was measured at day 6 after addition of the indicated concentrations of the drugs in 1% FBS. Sup Table 1. Thyroid histology of mouse GEMM models and frequency of metastasis. Sup Table 2. Classification of thyroid cancer cell lines based on YAP localization. Supplementary Methods. Sup Methods Table 1. Primers used for genotyping. Sup Methods Table 2. Primers for qRT-PCR.


ATTO594) and NOP receptor function with N/OFQ stimulated ERK1/2 phosphorylation. As an in vitro sepsis mimic we variably incubated cells with 100ng/ml Lipopolysaccharide and Peptidoglycan G (LPS/PepG). HUVECs express NOP mRNA and this was reduced by ~80% (n = 49) after 24–48 hours treatment with LPS/PepG. Untreated cells do not express surface NOP receptors but when treated with LPS/PepG the reduced mRNA was translated into protein visualised by N/OFQATTO594 binding (n = 49). These NOP receptors in treated cells produced an N/OFQ (1μM) driven increase in ERK1/2 phosphorylation (n = 20). One (of 50) HUVEC lines expressed NOP mRNA and receptor protein in the absence of LPS/PepG treatment. In contrast, HVSMC expressed NOP mRNA and surface receptor protein (n = 10) independently of LPS/PepG treatment. These receptors were also coupled to ERK1/2 where N/OFQ (1μM) increased phosphorylation. Collectively these data show that an in vitro sepsis mimic (LPS/PepG) upregulates functional NOP expression in the vascular endothelium. Activation of these endothelial receptors as suggested from in vivo whole animal work may contribute to the hypotensive response seen in sepsis. Moreover, blockade of these receptors might be a useful adjunct in the treatment of sepsis.Sepsis is a dysregulated host response to infection that can cause widespread effects on other organs including cardiovascular depression, hypotension and organ failure. The receptor for Nociceptin/Orphanin FQ (N/OFQ), NOP is expressed on immune cells and these cells can release the peptide. Exogenous N/OFQ can dilate blood vessels and this peptide is increased in animal and human sepsis. We hypothesise that NOP receptors are present on vascular endothelial cells and therefore provide the target for released N/OFQ to cause vasodilation and hence hypotension. Using human umbilical vein endothelial cells (HUVEC) and human vascular smooth muscle cells (HVSMC) freshly prepared from umbilical cords and up to passage 4, we assessed NOP mRNA expression by Polymerase Chain Reaction (PCR), NOP surface receptor expression using a fluorescent NOP selective probe (N/OFQ Sepsis is a dysregulated host response to infection that can lead to life-threatening organ dysfunction and is responsible for up to 11 million deaths worldwide per year . In certi/o proteins leading to a decrease in cyclic Adenosine Monophosphate (cAMP) production, activation of inwardly-rectifying potassium channels, closure of calcium channels and activation of mitogen-activated protein kinase pathways (MAPK) including ERK 1/2 N/OFQ binding [ATTO594 was incubated with the cells for 5 minutes at 4°C, following which unbound was cleared by perfusion with 4°C Krebs buffer. As we previously reported this low temperature eliminates receptor internalisation [ATTO594 and 488nm, for Hoechts live cell nuclear dye (blue). Specific binding of N/OFQATTO594 was determined through use of the NOP antagonist, SB-612111 (1μM) [ATTO594 [N/OFQreceptor , was add binding . Images lisation . Cells w[ATTO594 . In all [ATTO594  and usedFunctional NOP receptor expression was determined by measuring ERK1/2 phosphorylation in both HUVEC and HVSMC using Western blotting; this assay was selected as it requires relatively small amounts of tissue and produces an easily quantified readout. HUVEC or HVSMC were grown in 6-well plates until 70% confluent. Cells were then serum starved for 24hrs and variably treated with 100ng/ml LPS and 100ng/ml PepG for 24 or 48hours. Next cells were incubated in 37°C Krebs buffer for 30 minutes then challenged with 1μM N/OFQ for up to 30 minutes. Upon completion of the time course, the assay was terminated by removal of Krebs buffer, rinsing with ice-cold PBS and addition of ice-cold lysis buffer . Cells wFollowing denaturation, proteins were separated on 10% SDS-PAGE, transferred onto nitrocellulose paper by wet transfer and blocked in 10% milk TBS-T solution  for 2 hr at room temperature under gentle agitation. Membranes were subsequently incubated in primary phospho-ERK1/2 antibodies  and loading control antibody; vinculin , diluted in TBS-T overnight at 4°C. Primary antibody was removed and membranes washed 6 times, for 5 minutes per wash, in TBS-T. Membranes were incubated in HRP-conjugated secondary antibodies . Chemiluminescence detection, using the ChemiDoc™ MP imaging system  was used to visualise immune-reactive bands. Blots were analysed using the ImageLab software . All data is corrected for loading (Density of ERK/Density of Vinculin) and then measured as a ratio over basal activity .seeresults). Statistical analysis is described in the relevant Table and Figure legends and P-values ≤0.05 were considered statistically significant.All data are presented as mean±SEM from (n) experiments as noted in the results and Figure/Table legends. Confocal images are representative of (n) as noted. In HUVEC experiments PCR and confocal microscopy was performed in cell lines from 50 patients and 20 were analysed in Western blotting. In VSMC experiments PCR and confocal microscopy was performed in cell lines from 10 patients and 8 were analysed in Western blotting. The reduced number was selected as there was no LPS/PepG inducible signal  (Table 1). These changes at 24 and 48 hours equated to an approximate 80% decrease in NOP mRNA expression.Messenger RNA extracted from primary cultured HUVECs was used in qPCR to probe for NOP expression. All samples produced robust amplification of the housekeeper genes B2M and ELF2B1. In control conditions, NOP mRNA was present in all 50 cell lines tested demonstrating a mean ΔCATTO594, was used. As a positive control N/OFQATTO594 bound to the surface of HEKhNOP cells  and this was blocked by the NOP antagonist SB-612111  In 49 individual control HUVEC cell lines, 100nM N/OFQATTO594 failed to bind to untreated (100ng/ml of LPS/PepG) cells . In these 49 cell lines, treatment at both 24hrs  and 48hrs  with 100ng/ml LPS and 100ng/ml PepG treatment, led to binding of N/OFQATTO594. Binding of N/OFQATTO594 in these samples is blocked by the NOP-selective antagonist SB-612111 (1μM) . In PN5 cells, 100nM N/OFQATTO594 was able to bind to control samples  and could be blocked by SB-612111 (n = 5) . As noted above 100ng/ml of LPS/PepG treatment caused cell death in this line.Results from PCR demonstrated the presence of NOP mRNA in all 50 HUVEC cell lines, however the presence of mRNA does not necessarily equate to surface expression of a functional receptor. In order to determine the presence of NOP receptors the NOP-specific fluorescent ligand, N/OFQFig 3). In both instances, PN8  and PN5  demonstrated no change in their respective expression, with PN5 maintaining NOP expression from passage 2  through to passage 22 .Many studies using primary cultured HUVECs are with older passages. To determine whether long term culture changes NOP expression, PN5 (which expresses NOP in the absence of LPS/PepG) and PN8 (a cell line that required LPS/PepG treatment to induce NOP expression) were maintained over 20 passages with expression probed .There was no correlation between change in mRNA and N/OFQFig 4A). This is consistent with the lack of surface receptor protein demonstrated with N/OFQATTO594. When incubated for 24hr with 100ng/ml LPS/ PepG, N/OFQ-induced activation of ERK1/2 was seen after 10 minutes and continued to increase up to 30 minutes . In the HUVEC cell line, PN5, activation of ERK1/2 was seen in the untreated control sample, with activation beginning at 5 minutes and continuing through to 30 minutes post N/OFQ incubation (n = 5) . Measurement of ERK1/2 activity in PN5 HUVEC treated with 100ng/ml LPS/ PepG was not possible due to cell death. Full blots are provided in the Activation of HUVEC NOP receptors was measured by determining activation of the ERK1/2 pathway. When measuring activity in untreated control samples, 20 cell lines showed no activation over a period of 30 minutes when incubated with 1μM N/OFQ (t of 6.94 (Table 1). All 10 cell lines were treated with 100ng/ml of LPS/PepG for 24 hour and there was no change in NOP mRNA; ΔCt 6.75. Due to the lack of an inducible signal we limited the number of cell lines to 10.Messenger RNA extracted from primary cultured HVSMC was used in qPCR to probe for NOP expression. All cell lines produced robust amplification of the housekeeper genes B2M and ELF1. In control untreated samples, NOP mRNA was present in all 10 cell lines tested with a mean ΔCFig 6A) were subsequently tested for N/OFQATTO594 binding in confocal microscopy. In untreated samples N/OFQATTO594 bound to the cell surface of VSMC , with binding unaffected by 24hr incubation with 100ng/ml LPS/PepG . Binding of N/OFQATTO594 was blocked by the NOP-selective antagonist SB-612111 (1μM) .All ten cell lines . This series of experiments were performed on 8 cell lines. Full blots are provided in the Activation of HVSMC NOP receptors was measured by determining activation of the ERK1/2 pathway. N/OFQ (1μM) increased ERK1/2 phosphorylation after 2.5 minutes, peaking between 7.5–10 minutes, before returning to basal levels at 20 minutes  with neither the probe (large peptide) nor the antagonist being able to cross the plasma membrane. Moreover, as the experiments were performed at 4°C agonist driven NOP internalisation will not occur; we have confirmed this in high expressing recombinant systems [While the presence of NOP mRNA was detected in all cell lines, the presence of surface NOP receptor was found in only one (PN5) of the 50 untreated HUVEC cell lines. However, following incubation with LPS/PepG for both 24 and 48 hours NOP receptor was detected on the surface of these treated HUVEC via binding of the fluorescent probe N/OFQ systems . InteresIn 49 HUVEC cell lines, phosphorylation of ERK1/2 was used to detect functional activity following LPS/PepG induced NOP surface expression. In these samples, 1μM N/OFQ produced phosphorylation of ERK1/2 after 10 minutes, with ERK1/2 activity remaining elevated for the remainder of the 30 minute assay. In the untreated PN5 sample, N/OFQ produced an initial response after 5 minutes. This increased, throughout the course of the 30 minute assay.ATTO594, binding of the ligand to the cell surface was detected; this was totally blocked by the NOP antagonist SB-612111. These cell surface receptors were also coupled to ERK1/2 but the response was different to that seen in HUVECs. The very early response in muscle might suggest a G-protein driven event while the later response in the endothelium might suggest an arrestin driven event [In freshly isolated VSMC, NOP mRNA was detected in all cell lines tested, this was unaffected by LPS/PepG treatment for 24 hours) and there was no adverse consequences in terms of survival. When untreated VSMC were probed with N/OFQen event ; this wi hours anS2 Fig) we have confirmed that PN5 is HUVEC in origin; it was possible that this line was muscle that we know expresses NOP independent of LPS/PepG treatment. Our incidence of 1 in 50 compared favourably with incidence of post-partum infection at 3.9% [In this study a single cell line was shown to express NOP without the need for LPS/PepG stimulation. This cell line (termed PN5) displayed several distinct features not seen in the remainder of the HUVECs tested. Activation of ERK1/2 occurred earlier but was still different to that seen in muscle. The most striking difference was the sensitivity (cell death) to LPS/PepG challenge. Our ethics approval does not allow detailed collection of patients’ clinical or personal information so it is not possible to look back at pre-existing pathology, clinical course or concurrent medications for this subject. In a series of immunohistochemical analyses  there was no correlation between message and receptor. Based on N/OFQATTO594 binding (inset) expression peaked after 24 hours .HUVEC NOP mRNA and NOP receptor protein was measured by qPCR and N/OFQ(DOCX)Click here for additional data file.S2 FigImmunofluorescence Analysis of HUVEC cell Line PN5. In order to confirm the cell type identity of line PN5, immunofluorescence for the endothelial marker von-Willebrand Factor (vWF), the smooth muscle cell marker α-smooth muscle actin (α-SMA) and the fibroblast marker TE-7 with smooth muscle cell  and fibroblast (MRC5) positive controls. A secondary antibody-only control was included for all cell types. Green fluorescence indicates positive staining for the indicated marker. Nuclei were counterstained with Hoechst 33342 (blue). Images were obtained using with an Operetta CLS high-content imaging system (Perkin Elmer) using a 10x objective lens. Scale bar = 200μm.(DOCX)Click here for additional data file.S1 Raw data(PDF)Click here for additional data file.


G-quadruplex (G4) structures are critical epigenetic regulatory elements, which usually form in guanine-rich regions in DNA. However, predicting the formation of G4 structures within living cells remains a challenge. Here, we present an ultra-robust machine learning method, G4Beacon, which utilizes the Gradient-Boosting Decision Tree (GBDT) algorithm, coupled with the ATAC-seq data and the surrounding sequences of in vitro G4s, to accurately predict the formation ability of these in vitro G4s in different cell types. As a result, our model achieved excellent performance even when the test set was extremely skewed. Besides this, G4Beacon can also identify the in vivo G4s of other cell lines precisely with the model built on a special cell line, regardless of the experimental techniques or platforms. Altogether, G4Beacon is an accurate, reliable, and easy-to-use method for the prediction of in vivo G4s of various cell lines. A G-quadruplex G4) is a non-canonical structure that forms in guanine-rich sequences . The bas is a nonThe G4-detection techniques can be classified into two categories: experimental methods and computational methods. Early experimental techniques of G4-detection, such as NMR  and X-raExcept for the experimental methods discussed above, there are several computational methods  designed to predict G4 sequences. Most of these algorithms are used to detect the potential in vitro G4 sites without considering the specific cellular environment . The fir9 genome . The fur9 genome , using mtructure . The G-structure . After ttructure  and G4detructure , were prFollowing the development of in vivo G4 detection experiments, an individual computational method for predicting active G4 regions in cells, DeepG4, was presented . DeepG4 In this study, we proposed a cell-type-specific G4 prediction tool called G4Beacon, which implemented the Gradient-Boosting Decision Tree (GBDT) algorithm to predict if a G4-seq entry can fold into the quadruplex structure in a given cell type . The maiTo build and evaluate G4Beacon, the ATAC-seq data and in vivo G4 sequencing data were required for feature construction and dataset division. The critical problem was that there were few in vivo G4 sequencing data due to the high cost and experimental difficulty of in vivo G4 sequencing. We required cell lines with both high-quality in vivo G4 sequencing and ATAC-seq data, and, finally, three human cell lines—K562 (human chronic myelogenous leukemia cell line), HepG2 (human hepatoblastoma cell line), and MCF7 (human breast adenocarcinoma cell line)—were collected and used in this research.The human G4-seq data were downloaded from the Gene Expression Omnibus (GEO) database with the accession number of GSE110582 . We usedWe classified G4-seq entries into two parts, namely active G4 entries (positive samples) and inactive G4 entries (negative samples), for each cell line according to whether these G4-seq entries were supported by in vivo G4 experiments . We usedDue to the imbalance of positive and negative samples, which may affect the performance of traditional machine learning algorithms , traininG4Beacon took both the chromatin accessibility data (ATAC-seq) and the sequence data to construct features for each input G4-seq entry in the candidate dataset . To acquThe chromatin environment can influence the folding capability of in vivo G4s, as they were found to appear together with ATAC-seq peaks . The ATAMost of the existing G4 prediction models merely use the sequences from G4 sites to learn the sequence patterns of G4 structures ,22. Howehttps://github.com/microsoft/LightGBM, accessed on 2 November 2022) to implement our model workflow as it can provide categorical feature support and high training efficiency [We compared the performance of several machine learning methods, including Logistic Regression, Decision Tree, Random Forest, and Gradient Boosting Decision Tree (GBDT) , and finficiency .As mentioned in To explore whether different hyperparameters will have a significant impact on the model performance and to select the best model configurations, we utilized the grid-search method to optimize the hyperparameters for LightGBM using a 2-fold cross-validation experiment on the HepG2 cell line dataset  was applied to the training set before it was taken as the input of the GBDT classifier for training. Finally, the performance of the trained model was tested on the test set. We applied this evaluation workflow to all the cell line data (K562/HepG2/MCF7) that we collected. The sizes of each training set and test set were displayed . We compThe cross-cell-line experiment was applied for further evaluating the robustness of G4Beacon. One of the basic hypotheses of our study is that the active G4s in different cell lines exhibit similar chromatin accessibility and sequence patterns, and therefore the performance of our model should persist when the target samples come from different cell lines. In the cross-cell-line experiment, one cell line dataset was used as the training set and the remaining cell line datasets were used as the test sets. Similar to the one-cell-line experiment, the dataset used for training was preprocessed with over-sampling on positive samples and the datasets for the test remained unchanged. In this study, the HepG2 cell line data were utilized as the training set and the performance was tested on K562 and MCF7 cell line data.Accuracy, precision, recall, and F1-score were used as the basic criteria of prediction performance. Moreover, ROC and PRC, as well as AUROC and the average precision (AP), were also used to provide a more complete picture of the model’s performance. In both one-cell-line and cross-cell-line experiments, we repeated the process five times with different random seeds and obtained the mean ± standard error for each criterion.Besides the machine learning evaluation method, we also performed chromatin state analysis to further evaluate our method. Furthermore, we also compared the prediction results of G4Beacon with a recent in vivo G4 prediction tool, DeepG4 .https://github.com/raphaelmourad/DeepG4, accessed on 2 November 2022) and directly used for further comparative analysis [Consistent with the cross-cell-line experiment, we used the full HepG2 dataset balanced with the over-sampling method to train our G4Beacon model. The trained DeepG4 model was obtained from GitHub  when discriminating between the positive and negative samples .In the G4 ChIP-seq group experiments, we employed data from the K562 cell line and HepG2 cell line. For the K562 cell line, we found that models constructed with different feature combinations exhibited diverse characteristics . The seqThe HepG2 experiment had similar performance to that of the K562 experiment . The modThe performance of G4Beacon in K562/HepG2 experiments exhibited diverse characteristics. First, the sequence-only feature failed to provide enough information for in vivo G4 prediction, which means that the composition of sequences was not sufficient to characterize the formation ability of in vivo G4s. Second, the models using chromatin accessibility features provided excellent prediction accuracy in in vivo G4 prediction. Even on the test set with a skewed positive/negative ratio, G4Beacon could balance the performance in both precision and recall. Finally, adding a sequence feature to our approach improved the performance compared with the chromatin-accessibility-feature-only models. Although the sequence-only models performed poorly, integrating sequence information with chromatin accessibility information did improve the performance in our experiments.In the G4 CUT&Tag data experiment, we used MCF7 cell line data to construct the training set and the test set. In the MCF7 cell line experiment, G4Beacon with different feature selection approaches performed similarly as on K562 and HepG2 cell line data . The seqIn summary, we validated and confirmed that our model was powerful enough to predict in vivo G4s within both the training set and test set derived from the same cell line.In this study, we aim to propose a robust in vivo G4 predictor for different human cell lines. Therefore, it is indispensable to test the performance in the situation of a training set and test set coming from different cell lines. We designed a cross-cell-line train–test workflow to evaluate the performance of our model—that is, training on one cell line and testing on other cell lines. Specifically, we conducted a cross-cell-line experiment in which the model was trained on the HepG2 dataset and tested on the other two cell lines, i.e., the K562 cell line and MCF7 cell line. The entire data of each cell line were used in the above experiment. The data for model training were balanced using over-sampling methods, as for the training set in the one-cell-line experiment. As we had confirmed in the former experiments that the combined feature model exhibited the best performance, we then used ATAC and sequence-combined features in the cross-cell-line experiments.We found that the prediction model trained on HepG2 G4 ChIP-seq data (HepG2 model) in the cross-cell-line experiment had robust performance in predicting in vivo G4s in other cell lines . The HepOur G4Beacon approach has been proven to work robustly in the cross-cell-line experiment. Predictions on the K562 dataset, which was divided with the same in vivo G4 detection method data (G4 ChIP-seq), showed prominent precision as well as recall on the whole-genome scale test set. Moreover, G4Beacon can also perform robustly on a dataset (MCF7) constructed with different sequencing techniques. These results demonstrate that G4Beacon is equipped to learn the general ATAC-seq and surrounding sequence patterns of in vivo G4s detected by G4 ChIP-seq/G4 CUT&Tag experiments.Previous studies have shown that active G4s are preferentially located in active chromatin regions and are related to some histone modifications ,12,16. IWe characterized the histone modification around in vivo G4s predicted by G4Beacon and DeepG4, which could potentially justify the G4 prediction results as in vivo G4s are preferentially formed in active genomic regions ,16. We uAdditionally, we used a more stringent threshold  for the identification of active G4s and visualized the histone modification states around them, focusing on the most confident results of G4Beacon and DeepG4 . As a reIn summary, we described the histone modification states around the active G4s derived from G4Beacon and DeepG4. The results showed that the G4s predicted by G4Beacon were significantly enriched in open chromatin histone modification regions rather than closed modifications, which implied the characteristics of active G4s.The development of G4 detection methods, including G4-seq, G4 ChIP-seq, G4P-ChIP-seq, and G4 CUT&Tag ,10,13,15In this research, we focused on implementing the in vivo G4 predictions through a data-driven method. We developed an effective method called G4Beacon, which contained two core modules, namely the complete feature-construct module and the predictor module. In the feature-construct module, we used chromatin accessibility data, i.e., ATAC-seq data and the sequence data, as input to describe a candidate G4 sample. The predictor module was built based on a strong ensemble learning method, GBDT, and we used one of the widespread implements: LightGBM .Different from most of the existing G4 prediction tools that took only sequence data as input and predict non-cell-type-specific G4s, our model utilized the chromatin accessibility profiles, which reflect the intracellular environments of cells within G4 folding regions, as well as the surrounding sequences, which contain information about regulatory elements related to G4s, e.g., transcription factor binding sites. Due to the importance of in vivo G4 prediction, another deep learning algorithm has recently been proposed to characterize and predict in vivo G4s based on chromatin accessibility and sequence patterns, namely DeepG4 . AlthougTo verify the performance of G4Beacon, we profiled both machine learning evaluation experiments and bioinformatics analysis of histone modifications around the predicted active G4s. The machine learning evaluation experiments, including one-cell-line and cross-cell-line experiments, showed that G4Beacon not only performed well on data from one cell line but was also robust in cross-cell-line predictions . MoreoveHowever, the features that we considered in constructing the G4Beacon model are still inadequate to completely describe the cellular environment involved in G4 folding, which is a limitation of this model. Although the sequence patterns can be different between active and inactive G4s, the main differences should arise from the cell line environment where they are harbored—that is, the chromatin accessibility feature used in our research. With the developments in researching the environmental factors that can influence the formation of in vivo G4s, more useful information can be taken as input features. Even so, the framework of our G4Beacon can be generalized to support any type of sequential environment data. It is conceivable that G4Beacon can easily be employed to train on new expressive features, and thereby we can acquire predictors with better performance.In conclusion, G4Beacon is a very accurate, stable, and concise tool that can be used for the prediction of in vivo G4s.In this research, we proposed G4Beacon, a machine-learning-based in vivo G4 prediction method that utilized both the sequence and chromatin accessibility information to depict and identify the cell-type-specific active G4s. We tested G4Beacon in a one-cell-line experiment and a cross-cell-line experiment, which showed that our model was considerably accurate and robust in whole-genome in vivo G4 prediction. In summary, our method can quickly and extensively describe the landscape of in vivo G4s in existing cell lines and can facilitate genome-wide G4 studies and the discovery of their potential new biological functions.


Meanwhile, cell line U-87 was the most strongly sensitive to DOX when treated with 2 µM betulinic acid (change of EC50 = −45.1% ± 4.5%) in 2D culture. The combination of apple extract (E3) and DOX reduced the viability of HT-29 spheroids the most . Our study in 2D and 3D cultures showed that combining apple extract’s triterpenic complexes or individual triterpenic acids with DOX may sensitize chemotherapeutic drugs and increase the cytotoxicity effects in HT-29 and U-87 cell lines.Cancer cells’ resistance to anticancer drugs represents a major clinical problem and the most important failure of treatment. Combination chemotherapy is more effective than monotherapy due to additive or synergistic effects. The aim of our research was to assess the effects of the combinations of apple extract’s triterpenic compounds, individual triterpenic acids, and doxorubicin (DOX) on human colon adenocarcinoma (HT-29) and human glioblastoma (U-87) cell lines in 2D and 3D cultures. The effect of the combination of apple extracts, the triterpenic standards, and DOX against HT-29 and U-87 cell viability was tested by the MTT and spheroid growth assays. Cell line HT-29 was more sensitive to DOX when incubated with all tested apple extracts than DOX alone. Cell line HT-29 was the most strongly sensitive to DOX when it was treated with 5 µM oleanolic acid (change of EC Cancer is one of the prevailing reasons for morbidity and mortality worldwide. Based on Global Cancer Statistics data, in 2020, 18.1 million new cancer cases were established, with colon cancer representing 10.7% of all cases, and brain and central nervous system cancers 1.7% of all cases . A majorDoxorubicin is one of the most effective chemotherapeutic agents used routinely in the treatment of colon cancer and other solid tumors ,8,9. TheChemotherapy, regardless of its many adverse effects, is still the most acceptable way of curing cancer . Cancer Combination administration applying standard anticancer drugs and natural biological compounds extracted from the plant, or entire plant extracts, may be one of the most valuable strategies to defeat drug resistance. According to the scientific literature, most studies assess the effect of the combination of phenolic compounds and chemotherapy drugs on cancer cells. Shakibaei et al. showed that curcumin enhanced the effect of 5-fluorouracil on the colorectal HCT116 and HCT116 + ch3 cancer cell lines . StaedleThe aim of our research was to assess the effects of the combinations of apple extracts, triterpenic acids, and doxorubicin on HT-29 and U-87 cell lines in 2D and 3D cultures.This research involved the apple cultivars ‘Auksis’, ‘Kostele’, ‘Ligol’, and ‘Rubin’, which were cultivated in the orchard of the Institute of Horticulture, Lithuanian Research Centre for Agriculture and Forestry, Babtai, Lithuania . The apple trees were cultivated in 2020–2021.2 at 37 °C. Cell cultures were grown to 70% confluency, then trypsinized with 0.125% TrypLE Express solution before passage, and used until passage 20.The human colon adenocarcinoma cell line HT-29 and human glioblastoma cell line U-87 were purchased from the American Type Culture Collection . Human fibroblasts were provided by prof. Helder A. Santos . Cells were cultured in DMEM Glutamax medium supplemented with 10% fetal bovine serum (FBS), 10,000 U/mL penicillin, and 10 mg/mL streptomycin solution, in a humidified atmosphere containing 5% COAll solvents, reagents, and standards used were of analytical grade. Standards used in HPLC analysis: ursolic acid (UA), oleanolic acid (OA), corosolic acid (CA), and betulinic acid (BA), were purchased from Sigma-Aldrich GmbH . Solvents used in the study: 99.9% acetonitrile and 99.9% acetone, were acquired from Sigma-Aldrich GmbH , and 99.5% dimethyl sulfoxide (DMSO) was purchased from Scharlab S.L. . In this study, we used deionized water prepared by a Milli-Q  water purification system. Doxorubicin (DOX) hydrochloride was bought from Abcam , and 3--2,5-diphenyl tetrazolium bromide  was purchased from Buchs GmbH, Switzerland. The plasticware for cell cultures was obtained from Techno Plastic Products , Corning , and Thermo Fisher Scientific . Dulbecco’s modified Eagle high-glucose medium (DMEM Glutamax), TrypLETM Express reagent, fetal bovine serum (FBS), penicillin/streptomycin solution (100×), and phosphate-buffered saline (PBS) were obtained from Gibco . NanoShuttle magnetic nanoparticles were purchased from Nano3D Biosciences Inc. .Apple samples and dry triterpenic extracts were prepared using the method described by Butkeviciute et al. . In thisThe triterpenic compounds were identified and quantified by the HPLC-PDA method in the same manner reported in previous research by Butkeviciute et al. .50) values were calculated using the Hill equation. The EC50 value represents the concentration of a compound causing a 50% reduction of cancer cell metabolic activity.The effect of the combination of apple extracts, the triterpenic standards, and DOX against human colon adenocarcinoma HT-29 and glioblastoma U-87 cell viability was tested by the MTT assay, as reported by Grigalius and Petrikaite . The con50 (expressed in %) was established, which indicates how much DOX toxicity changed when the apple extracts and individual triterpenic acids solution were added to the medium. The experiments were repeated three times independently, and the results are presented as the means ± SD.The change of EC2 at 37 °C, until spheroids formed. After 48 h of incubation, the tested compounds and extracts were added. The DOX concentration used in spheroids was 20 nM, and the concentrations of tested material were as follows: 2 µM of triterpenic acids, and 30 µg/mL of extracts. In addition, control groups were included: the spheroids not treated with any substances or only with tested triterpenic acids and extracts (without doxorubicin).Spheroids were formed by a magnetic 3D bioprinting method, as described elsewhere . BrieflyPhotos of spheroids were taken every 48 h, simultaneously changing the medium with tested materials. The effect of the combination of apple extract’s triterpenic compounds, individual triterpenic acids, and DOX in 3D glioblastoma and colorectal carcinoma cells was analyzed by measuring the diameter change of spheroids using ImageJ software  and by the change of cell viability in spheroids by the MTT assay. The experiments were repeated three times independently, and the results are presented as the means ± SD.p < 0.05.The statistical analysis of the study data was performed using Microsoft Office Excel 2013  and SPSS 25.0  computer software. All the experiments were performed in at least triplicate independent measurements and the obtained values were reported as mean ± standard deviation. Tukey’s multiple comparison test was used. The differences were held as statistically significant at 50 varied from −43.2% ± 2.2% to −53.0% ± 1.4%), and there were no statistically significant differences between them. Cell line U-87 became even less sensitive to DOX when treated with all apple extracts (change of EC50 varied from 7.2% ± 0.4% to 34.2% ± 1.7%)  a.50 varied from −64.6% ± 4.4% to −43.9% ± 10.7%) (50 = −64.6% ± 4.4%) and with 5 µM ursolic acid (change of EC50 = −61.9% ± 8.8%) (50 = −43.9% ± 10.7%) or with 2 µM betulinic acid (change of EC50 = −49.3% ± 9.0%), though the effect was still synergistic (50 varied from −45.1% ± 4.5% to −16.0% ± 2.4%) (50 = −45.1% ± 4.5%). We found that cell line U-87 was not sensitized to DOX when treated with 5 µM ursolic acid  b. Cell l ± 8.8%) b. Cell lergistic b. Cell l ± 2.4%) b. Cell llic acid b.Miscellaneous fruits, including apples, can be held as possible sources of a chemosensitizer . For somMost researchers have invoked 2D culture models, which have shown restricted opportunities in the translational to clinical practices for their deficiencies in simulating the complexity of the tumor microenvironment . The appAn analysis of 3D cell cultures showed that most combinations of apple peel extracts and DOX  reduced HT-29 spheroids’ size, compared to spheroids treated with DOX alone . HT-29 sUnlike the previously described research results in 2D cultures, the effect of the combinations of apple extract′s triterpenic complexes and DOX on the size of U-87 spheroids was not revealed b. In ourDespite small differences in spheroid size, the MTT assay in spheroids showed more expressed differences between groups in terms of cell viability . After cOf all tested combinations, the betulinic acid and DOX combination most efficiently reduced the viability of HT-29 spheroids  a. U-87 sSilybum marianum (L.) Gaertn. Seeds’ standardized extract with DOX or paclitaxel [Solanum nigrum leaf extract and cisplatin, DOX, docetaxel, or 5-fluorouracil [Artemisia princeps var. orientalis leaf extract and DOX [Some authors reported that combinations of plant extracts and chemotherapeutic agents might act additively or synergistically. In recent decades, many studies have been conducted evaluating the effects of the combination of DOX and plant extracts on cancer cell lines. Previous studies have described more synergistic interactions between plant extracts and anticancer drugs, such as clitaxel , Solanumrouracil , and Art and DOX .In previous studies, we evaluated the effect of apple extract’s triterpenic and phenolic compounds on the viability of human colon adenocarcinoma HT-29 and human glioblastoma U-87 cell lines . During In our study, we found the different effects of apple extracts and individual triterpenic acids in 2D and 3D human colon adenocarcinoma and human glioblastoma spheroids’ cultures. As expected, the compounds were more active in cell monolayers than in spheroids. We determined that the human colon adenocarcinoma HT-29 cell line cultivated in a monolayer and spheroids was more sensitive to DOX when incubated with all apple extracts  and individual triterpenic acids  than DOX alone. Meanwhile, cell line U-87 in 2D cultures became even less sensitive to DOX when treated with all apple extracts and ursolic acid. The combination of apple extracts and DOX had no significant effect on the viability of U-87 cells in 3D cultures, compared to spheroids treated with DOX alone. After comparing the composition of the tested apple extracts, we found that the highest amounts of individual triterpenic compounds  were found in the apple extract, marked E1 . HoweverSome authors described the effects of the combinations of individual triterpenic compounds and chemotherapeutic agents in cancer cell lines in 2D cultures. Bao et al. determined the synergistic interaction between oleanolic acid, its derivatives, and paclitaxel in breast MDA-MB-231 cancer cell lines . Villar We hypothesize that possibly, different apple extract concentrations of individual triterpenic acid induce different mechanisms of action in HT-29 and U-87 cell lines. The success of the combinations of triterpenic compounds and chemotherapeutic agents on cancer cells may be accompanied by various mechanisms of action and depend on the selected cancer cell types ,41. Our Triterpenic compounds not only demonstrated a relevant apoptotic effect on cancer cells but also sensitized them to chemotherapeutic drugs . Blanco In some incidences, it is possible to bypass gained chemoresistance by combination therapy of anticancer agents with chemosensitizers such as triterpenic compounds. The published scientific results confirm that the combinations of individual triterpenic compounds with a chemotherapeutic drug can increase its sensitivity to cancer cells and increase cytotoxic activity. As a result, the desired effect can be achieved with a lower dose of the drug, and combined chemotherapy can reduce the consequences of side effects.We evaluated that human colon adenocarcinoma HT-29 and human glioblastoma U-87 cells were sensitive to DOX when treated with apple extracts and individual triterpenic acids in 2D and 3D cultures. We determined that the HT-29 cell line was most strongly sensitive to DOX when treated with all tested apple extracts and triterpenic acids, compared to U-87 cells. HT-29 cells were most strongly sensitive to DOX when treated with 5 µM oleanolic acid. On the contrary, U-87 cells were most strongly sensitive to DOX when treated with 2 µM betulinic acid. The 3D cell cultures study showed that a combination of betulinic acid and DOX most efficiently reduced the viability of HT-29 and U-87 spheroids, compared to spheroids treated with DOX alone. Our study in 2D and 3D cultures showed that combining natural-origin apple extracts or individual triterpenic acids with DOX may sensitize it and increase the cytotoxicity effects in HT-29 and U-87 cell lines. The obtained results are important in combination chemotherapy and may help to decrease the effective dose of anticancer agents, overcome the resistance, and diminish possible side effects.


BAP1 loss and monosomy of chromosome 3 are present in patients with high risk of metastasis. MEK-inhibitors do not significantly block UM progression. Combinations of the MEK inhibitor trametinib and different classes of drugs targeting YAP/TAZ were used to overcome resistance. Combination of trametinib and cerivastatin were synergistic in vitro and in vivo in BAP1 mutated and chromosome 3 monosomic uveal melanoma cell lines.Uveal melanoma is a rare and aggressive disease. Gα-proteins GNAQ and GNA11 are driver mutations that activate MAP kinase and YAP/TAZ pathways. BAP1-mutated UPMM3 cell line. The combined treatment reduced ERK and AKT phosphorylation, increased the inactive, cytoplasmatic form of YAP and significantly impaired the growth of UM cells with monosomy of chromosome 3 in NSG mice. Conclusion: Statins can potentiate the efficacy of MEK inhibitors in the therapy of UM.Background: Metastatic uveal melanoma (MUM) is a highly aggressive, therapy-resistant disease. Driver mutations in Gα-proteins GNAQ and GNA11 activate MAP-kinase and YAP/TAZ pathways of oncogenic signalling. MAP-kinase and MEK-inhibitors do not significantly block MUM progression, likely due to persisting YAP/TAZ signalling. Statins inhibit YAP/TAZ activation by blocking the mevalonate pathway, geranyl-geranylation, and subcellular localisation of the Rho-GTPase. We investigated drugs that affect the YAP/TAZ pathway, valproic acid, verteporfin and statins, in combination with MEK-inhibitor trametinib. Methods: We established IC50 values of the individual drugs and monitored the effects of their combinations in terms of proliferation. We selected trametinib and cerivastatin for evaluation of cell cycle and apoptosis. Synergism was detected using isobologram and Chou–Talalay analyses. The most synergistic combination was tested in vivo. Results: Synergistic concentrations of trametinib and cerivastatin induced a massive arrest of proliferation and cell cycle and enhanced apoptosis, particularly in the monosomic,  B-Raf Proto-Oncogene (BRAF), NRAS Proto-Oncogene (NRAS), and Neurofibromin 1 (NF1) [G Protein Subunit Alpha Q (GNAQ) and 11 (GNA11), and BRCA1- associated Protein 1 (BAP1) [Protein Tyrosine Kinase 2 Beta (PTK2B) have been identified [alpha G-protein subunits GNAQ and GNA11, are found in most primary UM in a mutually exclusive pattern [BAP1, Splicing Factor 3b Subunit 1 (SF3B1), and Eukaryotic Translation Initiation Factor 1A X-Linked (EIF1AX) are associated with high, intermediate, and low metastatic risk, respectively [Polycomb gene repression [BAP1 allele.Uveal melanoma (UM), the most common primary intraocular tumour in adults, is characterized by marked variability in its ability to metastasize. Up to half of the patients with UM develop distant metastases, most commonly in the liver . Unlike 1 (NF1)  in CM; a1 (BAP1) ,7,8 in Uentified . Mutatio pattern . Mutatiopression ,13, actiGNAQ and GNA11 activate the classical G-protein signalling cascade via inositol-3-phosphate, diacyl-glycerol, and cyclic AMP leading to the stimulation of mitogen-activated protein (MAP) kinases, protein kinase B (Akt), and C (PKC), phosphoinositide 3-kinase (PI3K) and the mechanistic target of rapamycin (mTOR) . DespiteYAP/TAZ activity is under the direct control of cell shape and polarity dictated by the cytoskeletal structure . YAP/TAZStatins are potent inhibitors of the mevalonate pathway and are used in clinical practice to prevent hypercholesterolemia-derived cardiovascular and coronary heart diseases . The mevStatins, used to inhibit the HMGCR activity, also antagonise isoprenylation and inhibit nuclear localisation and transcriptional activity of YAP/TAZ, mediating a potential anti-cancer activity ,27. A poBAP1 mutation [The main oncogenic functions of YAP/TAZ have been attributed to their interaction with the TEAD transcription factor. The ophthalmological drug verteporfin, an inhibitor of the YAP/TEAD interaction, has shown efficacy in vitro on UM cell lines, except on those bearing mutation .BAP1-mutated cells [Histone acetylation controls gene expression by modulating the access of transcription factor components to genomic regions. The histone deacetylases (HDACs) levels are increased in cancer . Target ed cells ,33. A phBAP1 allele, as a model.With the aim to identify drug combinations that can be used in the treatment of metastatic UM, we analysed those expected to inhibit both MAP-kinase and YAP-signalling and to block UM proliferation. In particular, we focused on the effects of statins and used verteporfin and valproic acid drugs that potentially block YAP-signalling in parallel for comparison. Verteporfin is used to treat macular degeneration and valproic acid is under clinical investigation for adjuvant therapy of UM. The most potent statin and trametinib combination, cerivastatin and trametinib, was tested in vivo using UPMM3, a cell line with monosomy of chromosome 3 (Chr3) and a loss-of-function mutation of the remaining 2.The human UM cell lines 92.1 , MEL270 Trametinib  was dissolved in DMSO at a final concentration of 40 mM, aliquoted, and kept at −80 °C. Atorvastatin, simvastatin, cerivastatin, and verteporfin  powders were dissolved with DMSO at a final concentration of 10 mM, aliquoted, and kept at −20 °C. Valproic acid  was dissolved in deionised water at a final concentration of 1 M and kept at −20 °C.Cells were seeded in 96-well, flat-bottom plates . The following day, increasing drug concentrations and their combinations were added to the cell culture and incubated for 72 h. Cell viability was tested using a 3--2, 5-diphenyl tetrazolium bromide (MTT) assay, . Optical density (OD) was read on a multiwell scanning spectrophotometer  at 570 nm. All experiments were performed three times. The inhibitory concentration that led to 50% growth reduction (IC50) was calculated using a wide range of drug concentrations by the Graph Pad Prism v 9.4 software . The synergism evaluation was performed using the MTT cell viability results obtained after single and combined treatments. The MTT assay was used to measure cellular metabolic activity as an indicator of cell viability, proliferation and cytotoxicity. Since none of the drugs were expected to directly affect mitochondrial activity, the formation of formazan can be used as a proxy for proliferation in UM cell lines. Drug combinations were evaluated following the method established by Chou and Talalay  and the 5 cells were washed in PBS, permeabilised in cold 70% ethanol, and incubated overnight at 4 °C in the dark. After washing with PBS, the cells were incubated in 1 ml of propidium iodide (PI) staining solution for 30 min at RT in the dark. The cell cycle was determined using a flow cytometer  and analysed by ModFit LT v3.0  software.UM cells were seeded in 24-well plates and treated with either trametinib and cerivastatin at IC50 or different synergistic concentrations alone or in combination for 72 hrs. Cells were harvested and 1 × 10Apoptosis was detected with Annexin V-fluorescein isothiocyanate (FITC) and PI, accordingly to the manufacturer’s instructions , and analysed by FACScan Flow cytometer and CellQuest  software.Total proteins were extracted using Complete Lysis buffer containing, proteases inhibitors (04719956001 Roche) and phosphatase inhibitors (04906845001 Roche). Preparation of nuclear extracts was performed by using NE-PER™ nuclear and cytoplasmic extraction reagents according to the manufacturer’s instructions. The Western blot of cell lysates was performed as previously described . Antibodscid Il2rgtm1wjl/SzJ mice were obtained from Charles River . The animals were housed in pathogen-free conditions, and experiments were performed according to the National Regulation on Animal Research Resources and approved by the Institutional Review Board (Aut n°190/2021-PR (risp prot.22418.151)). UPMM3 cells (107) were injected subcutaneously in 16 mice that were randomised in 4 groups of 4 mice each. Trametinib and cerivastatin were initially dissolved in DMSO and diluted into an aqueous pooled dose containing a final concentration of 0.5% hypromellose (Sigma-Aldrich) and 0.05% Tween-80 (Sigma), in saline. Control animals received the vehicle. Final maximal DMSO concentration was 8.8% v/v. Mice weight and tumours were measured weekly. Tumour volume was calculated as follows: V = ½ × L × W × H.Six-weeks old NOD.Cg-Prkdchttp://www.ncbi.nlm.nih.gov/geo/, accessed on 26 January 2023), under accession number GSE212219.UPMM3 cells were treated for 24 h with trametinib 10 nM, or cerivastatin 0.125 µM or the combination of these drugs. The experiment was repeated three times. RNA was extracted from cell lines using RNeasy Plus mini kit . RNA quality was assessed with Nanodrop and BioAnalyser tools . cDNA, ds-cDNA, and cRNA synthesis and fragmentation were performed using the 3’ IVT Express Kit . Hybridisation, washing, and staining were performed using the GeneAtlas . All micro-array data are MIAME compliant. The dataset, corresponding to 12 cell files is available from the GEO database . Analyses were performed using PRISM v 9.4 .The paired or unpaired Student’s Micro-array gene expression data were analysed in R/BioConductor. Quantile normalisation was performed using RMA , differeMAPK-targeted therapy has so far not been successful in UM as a single agent. With the objective to find drugs that can be combined with inhibitors of MAPK to improve their effectiveness, we decided to evaluate the cytotoxic effects of drugs targeting the oncoprotein YAP/TAZ in UM cell lines because the YAP/TAZ pathway plays an important role in UM development . We assessed the effects of statins that target the mevalonate/cholesterol biosynthetic pathway and interfere with YAP protein activation and that inhibit YAP nuclear translocation . We alsobona fide UM cell lines with GNAQ or GNA11 mutations  and OMM2.5 (MUM) were derived from the same patient.We selected the following 6 human utations : 92.1, MCells were treated with different concentrations of each drug for 72 h. Trametinib showed an IC50 value in the nanomolar range of concentrations. The cell line MEL270 was the most sensitive cell line, with the lowest IC50 , OMM1 and OMM2.5 were the least sensitive cell lines  with OMM1 showing the highest IC50 . PrimaryWe tested the combination of trametinib with cerivastatin combining both drugs at concentrations below IC50. We used the method described by Chou and Talalay  to calcuBAP1-mutated UM cell lines (UPMM2 and UPMM3) representative of high-risk primary UM and on OMM2.5 derived from a liver metastasis , respectively, induced 40% of apoptosis. A higher percentage of cells underwent apoptosis when the IC50s of the two drugs were combined A. The ceTreatment with trametinib blocked the cell cycle in the G0/G1 phase in all UM cells tested. Synergistic combinations of trametinib and cerivastatin caused the same cell cycle arrest observed when using the IC50 concentrations of trametinib B.We next focused on the possible signal transduction pathways involved in the increased cytotoxic activity mediated by the synergistic combination of trametinib and cerivastatin treatment. Cleaved PARP-1 and active caspase3 were only expressed in the synergistic combination , suggestB4GALT5, IDH1 and RASSF3 displayed an intermediate level of expression compared with cerivastatin and trametinib alone , cerivastatin  or trametinib and cerivastatin for 57 days (until day 64). The end of treatment was followed by 15 days of observation. Strong inhibition of tumour growth was observed for trametinib-treated mice. The addition of cerivastatin determined a significantly stronger inhibition of tumour growth compared with mice treated with trametinib alone (p = 0.03, Mice showed neither signs of toxicity nor loss of body weight (mice, while it remained not detectable in trametinib and cerivastatin-treated mice. Indeed, in days 71, 77 and 81, tumours from mice treated with trametinib and cerivastatin remained significantly smaller than those from trametinib group (p = 0.02, p = 0.04, p = 0.01, respectively, mice treated with cerivastatin presented a trend to smaller tumours at the end of the treatment compared with control mice although this did not reach statistical significance.In order to validate the effects of trametinib and cerivastatin combination on UM cells in vivo we generated xenografts of a primary monosomic y weight C. DuringGNAQ or GNA11 that activate two different oncogenic signalling pathways, the MAP/MEK-kinase and the YAP/TAZ pathways. The latter, considered important for organ growth control, has only recently gained more attention in oncology. Oncogenic mutations of GNAQ and GNA11 lead to dephosphorylation of YAP and TAZ, with nuclear translocation of YAP and increased cell growth and anti-apoptotic activity [In stark contrast to what has been obtained for cutaneous melanoma, targeted therapy using MAP-kinase and MEK-inhibitors  and immuactivity .BAP1 than in cells in which BAP1 function is abolished by mutations and monosomy of chromosome 3, as is typical for UM with high metastatic risk [Given the activation of two different oncogenic pathways, the association of different classes of drugs targeting signalling downstream of GNAQ or GNA11 has been proposed to block UM cell growth ,58. Drugtic risk . In additic risk .BAP1-mutated UPMM3 cell line. HDAC inhibitors such as VPA also have inhibitory effects on UM cell growth [BAP1-mutant UM in a mouse model [In our hands, verteporfin displayed synergistic activity with trametinib in three of the six cell lines tested, including the monosomic l growth . More rel growth . Quisinose model . Though se model . We showse model ,62. In oEpidemiological studies have shown evidence of reduced cancer incidence and mortality with statins, though their anti-cancer properties remain under investigation . High thBAP1-mutated UM cell lines, models of UM at high risk of metastasis. OMM2.5 cells, derived from an UM liver metastasis, are also sensitive to the combination of trametinib and cerivastatin, although at a lower level compared with the monosomic/BAP1 mutated cells. The simultaneous exposure of UM cells to cerivastatin and the MEK inhibitor allowed us to obtain the IC50 at trametinib doses 100-times lower in the combination, than with trametinib alone. This translates into enhanced efficacy with possibly more manageable toxicity when performing clinical trials. The synergic concentration of cerivastatin was six-fold lower than the IC50 value of the drug alone, an important fact since cerivastatin has been discontinued for clinical use as a cholesterol-lowering medication due to its toxic effects [We have shown that statins have antiproliferative effects in the majority of the UM cell lines tested. The most potent effect was obtained with cerivastatin. We observed synergistic effects of trametinib and cerivastatin in UPMM3 and UPMM2 monosomic and  effects .mice led to the development of tumours in 100% of mice. The oral administration of trametinib and cerivastatin significantly reduced tumour growth compared with control and to the two drugs used as a single treatment with no evidence of toxicity. Cerivastatin alone did not significantly affect tumour growth. Trametinib alone, instead, reduced the size of tumours in mice, confirming an inhibitory effect of trametinib on UM growth in vivo [mice treated with trametinib and cerivastatin but not in the mice treated with trametinib used as a single drug.Transplantation of the UPMM3 cell line in highly immunologically deficient  in vivo . HoweverThe synergistic treatment in vitro of UPMM3 cells affected YAP translocation into the nucleus and involved inhibition of ERK1/2 activation and AKT signalling. Notably, the upregulation of AKT signalling, a potential mechanism of escape from MEK inhibition , is blocRASSF3, a paralog of RASSF1 that has already been implicated as a tumour suppressor in UM [KRAS and RAS-related genes appear upregulated probably as a consequence of the unavailability of the correct post-translationally modified proteins caused by the mevalonate block [Mice in which the gene encoding the molecular target of statins, HMG-CoA reductase, has been disrupted, develop rhabdomyolysis spontaneously [The reduced expression of or in UM , followior in UM ,71, an aor in UM . KRAS ante block ,53. All te block . Rhabdomte block . In manyte block  or gemfite block . The exate block . Mice inaneously . Cerivasaneously . TherefoWhen considering cerivastatin for treating MUM, the patient’s specific risk profile must be considered. Patients at high risk of developing statin-induced rhabdomyolysis can be identified ,79. The We propose to test the combination of trametinib and cerivastatin in clinical trials. This combination could improve the survival of metastatic uveal melanoma patients while waiting for the development of specific GNAQ and GNA11 inhibitors and in the rarer cases of GNAQ/11 wild-type metastatic uveal melanoma.


Esophageal squamous cell carcinoma is the most common type of esophageal cancer and accounts for 5% of malignant tumor deaths. Recent research suggests that chronic inflammation and DNA damage may drive the onset of esophageal squamous cell carcinoma, implying that lowering chronic inflammation and DNA damage compounds may provide chemo-prevention. According to epidemiological and experimental evidence, selenium is linked to a lower risk of several malignancies, including esophageal squamous cell carcinoma. However, its exact mechanism is still unclear. In the present study, we used cell lines and a 4-NQO mice model to explore the anti-cancer mechanism of four types of selenium. Our findings indicated that selenium inhibited the proliferation, colony formation, and ROS level of ESCC cell lines in a time-dependent manner. Intriguingly, selenium treatment impeded 4-NQO-induced high-grade intraepithelial neoplasia and reduced the number of positive inflammatory cells by preserving DNA from oxidative damage. In addition, selenium significantly decreased the expression of Ki-67 and induced apoptosis. This study demonstrates that selenium has a significant chemo-preventive effect on ESCC by reducing high-grade dysplasia to low-grade dysplasia. For the first time, selenium was shown to slow down the progression of esophageal cancer by lowering inflammation and oxidative DNA damage. Esophageal squamous cell carcinoma (ESCC) is the deadliest form of gastrointestinal malignancy and is the eighth most common cancer worldwide. It is the most prevalent in Asia and Africa, but North America and Europe are experiencing a rapid increase in cases ,2. This Several previous studies indicate that inflammation accelerates cell cycle progression, cell proliferation, tumor vascularization, and the evasion of apoptotic cell death, all of which play a role in cancer initiation and progression . Damage Selenium (Se) is a vital and unique trace element that helps to prevent various tumor malignancies, including ESCC ,11. PrevWe first examined three established human ESCC cell lines, KYSE 150, KYSE 520, and CSEC 216, for their sensitivity to MSA, MSC, and Se-Met in comparison with sodium selenite using CCK8 cytotoxicity assays. The cells were treated with 1–100 µM selenite, 10–1000 µM MSC or Se-Met, and 0.001–6 µM MSA for 2 and 6 days. All three cell lines were susceptible to selenite, which induced a dose- and time-dependent growth inhibition A. At theThe anti-proliferative capacity of selenium was also evaluated by colony formation assay. Three ESCC cell lines treated with 6 µM (selenite), 100 µM , and 2 µM (MSA) showed an inhibition of their colony-forming efficacy during 14 days of culture with a regular change of normal medium, every three days E–G, whicp < 0.001) and large size of lesions , compared to untreated mice, respectively. Meanwhile, mice treated with selenium compounds had a significantly lower number of lesions: selenite group , MSA group , MSC group , Se-Met group , MSA group , MSC group , Se-Met group , which is thought to be the most effective chemical for inducing in animals histological alterations similar to those seen in humans. A smooth surface, normal thickness, and flexibility were observed in the untreated esophageal tissue of mice. However, we observed obvious lesions in all 4-NQO-treated mice. The effects of selenium compounds were quite remarkable B. Upon gMoreover, we observed microscopical morphological changes in esophageal tissues. We found that the esophageal epithelium of the 4-NQO-treated group exhibited high-grade intraepithelial neoplasia (HGIN) and more inflammatory cell infiltration than the untreated group. At the same time, selenium compounds  showed low-grade intraepithelial neoplasia (LGIN). Nevertheless, the range of esophageal epithelial lesions in the selenite group was relatively closer to high-grade intraepithelial neoplasia. Similarly, the number of abnormal esophageal epithelial lesions in the MSA group was relatively lower, and inflammatory infiltration was also relatively lower E. This rTo gain insights into the possible mechanisms underlying the inhibitory effects of selenium compounds in ESCC cell lines . The present study assessed their effects on apoptosis by flow cytometry. Annexin V-positive (early and late apoptosis) cells were considered the apoptotic population. ESCC cell lines were treated with selenium compounds—selenite (6 µM), MSA (2 µM), MSC (100 µM), and Se-Met (100 µM)—for 2 and 6 days. Our results indicate that all selenium compounds significantly increased cell apoptosis in KYSE 150 A,B, KYSENext, we examined the morphology of three ESCC cell lines treated with selenium compounds for 2 and 6 days. The results show that the number of cells in an unscratched area reduced. The cells showed typical apoptotic morphology, including a detachment from the bottom of the culture dish and a change in cell shape  under a phase-contrast microscope C,D and . Our resWe identified whether selenium compounds could also reduce proliferation and induce apoptosis in the esophageal epithelium tissue and investigated the proliferative status of these esophageal lesions after selenium treatment by detecting Ki-67 expression. A weak nuclear immunoexpression was observed in mice of the untreated group. When mice were exposed to 4-NQO, cell proliferation was highly elevated in the basal cells of the esophageal epithelium. In contrast, there was a significant decrease in Ki-67 expression in epithelial cells following selenium compound treatment E,F. To f2O2 increased nuclear fluorescence regarding the control. Thus, H2O2 seems to increase inflammation in both cell lines. In contrast, the combined exposure of H2O2 and selenium compounds markedly decreased nuclear fluorescence signals to those of only H2O2 treatment  in the esophagus tissues of the 4-NQO group compared with those in the untreated group  per analyzed field were significantly higher  accumulation plays a vital part in developing human esophageal cancer since ROS produces oxidative alterations of cellular macromolecules, such as DNA, proteins, and lipids ,8. We th2O2 for 16 h. The treatment of cells with H2O2 markedly increased the number of γ-H2AX foci  . Therefo2AX foci  and nucl2AX foci  relativep < 0.001). However, a decrease in γ-H2AX immunoreactivity was observed in mice that received selenium compounds: selenite group , MSA group , MSC group , Se-Met group  (p < 0.0003), MSA group , MSC group , Se-Met group ,  I,J compa0.0001), K,L that Esophageal cancer is one of the most common malignancies. ESCC occurs at very high rates in certain regions of China . CurrentOne of the physiological changes in cancer cells is their continued development paired with their loss of apoptotic mechanisms, which is associated with increased cell proliferation . A signi2O2-treated human immortalized esophageal epithelial cell lines.Inflammation is a natural aspect of the human body’s reaction to tissue damage when inflammation becomes persistent and is thought to be a significant risk factor for various human malignancies, including cancer . Our preDNA damage can be caused by a variety of hazardous substances, including inflammatory cytokines . ReactivSodium selenite (selenite), Se-(methyl) selenocysteine hydrochloride (MSC), selenomethionine (Se-Met), and methylseleninic acid (MSA) were purchased from Sigma . Dulbecco’s Modified Eagle Medium (DMEM), fetal bovine serum (FBS), trypsin–EDTA Roswell Park Memorial Institute (RPMI) 1640 Medium, keratinocyte–SFM medium, and an Epilife medium were acquired from Gibco . Penicillin and streptomycin were bought from Sigma . WST-8  (CCK 8) was purchased from . The carcinogen 4-NQO was purchased from Sigma Aldrich . Pentobarbital sodium was purchased from Sigma . Annexin V-FITC/PI Apoptosis Detection kit was purchased from . 2, 7-dichlorodihydrofluorescein diacetate (DCFH-DA) was obtained from . Antifade Mounting with DAPI was obtained from Vector lab, Inc. . Antibodies against Ki67 (#12202), γH2AX (#9718), NF-ĸB (#8242), CD45 (#70257), CD4 (#25229) and CD8 (#98941) were purchased from Cell Signaling Technology . 8-OHdG (bs-1278R) was purchased from Bioss Biotechnologies, Beijing, China. Normal goat serum was bought from ZSGB-BIO, ZLI-9022, Beijing, China. Secondary antibodies (Max Vision HRP rabbit kit) were acquired from MXB Biotechnologies, Kit-5004, Fuzhou, China. Immunofluorescence secondary antibodies were obtained from . DAB Kit was obtained from MXB Biotechnologies, DAB-0031, Fuzhou, China).2. KYSE 150 and KYSE 520 were maintained in RPMI 1640 with 10% fetal bovine serum and antibiotic mixture at 37 °C in a humidified incubator containing 5% CO2. Cells were passaged upon reaching 70% to 80% confluency. Cells at passages 4–8 were used for all experiments.Three ESCC cell lines  and two human esophageal immortalized epithelial cell lines (NE2 and NE6) were included in this study. The ESCC cell lines were gifts from Shantou University Medical College . CSEC 21NE2 and NE6 cell culture: Prof. George Tsao kindly provided the human immortalized esophageal epithelial cell lines (NE2 and NE6) from Hong Kong University. NE2 and NE6 cells were grown in a defined keratinocyte–SFM medium and an Epilife medium supplemented with a defined keratinocyte–SFM growth supplement. NE2 cells were accompanied with an additional 1% FBS. Cell cultures were maintained at 37 °C in a humidified atmosphere of 95% air and 5% CO2. The culture medium was renewed every three days. selenite, MSC, MSA, and Se-Met were prepared in double-distilled water, filter sterilized, and then stored in 100 µL aliquots and kept at −20 °C in a freezer. A fresh vial was thawed for each use. All experiments were performed with mycoplasma-free cells. All human cell lines were authenticated within the last 3 years using STR profiling.Cell viability was estimated by CCK colorimetric assay and carried out as previously described . See MetSingle-cell suspensions were generated for each ESCC cell line, and a specified numbers of cells were seeded into six-well tissue culture plates. Then, cells were exposed to different doses of Se compounds  for 2 weeks at 37 °C. Culture medium was replaced every three days until the appearance of colonies. The cells were fixed with 4% buffered formalin for 15 min and then stained with 1% crystal violet  for 30 min. The plates were gently washed with PBS. Cell clusters with >50 cells were considered as a colony, and colonies were imaged and counted by the software ImageJ.Cell apoptosis was quantified using the Annexin V-FITC/PI Apoptosis Detection kit following the manufacturer’s protocol. Briefly, after indicated treatment, cells of each ESCC cell line were collected by centrifugation, washed twice with ice-cold PBS, centrifuged at 1000 rpm for 5 min, then gently resuspended in 500 µL of binding buffer. Then, 5 µL Annexin V-FITC and 5 µL PI were added to each sample. The cell samples were incubated in the dark for 15 min at room temperature, detected using flow cytometry , and analyzed using BD Accuri C6 plus software. The apoptotic rate was calculated as the percentage of early + late apoptotic cells.The intracellular ROS level of three ESSC cell lines  was determined at culture days of 1 and 3 using a 2, 7-dichlorofluorescin-diacetate (DCFH-DA) based kit following the manufacturer’s protocol. See Immunofluorescence staining was performed against phospho-H2AX, 8-OHdG, to examine the effect of Se compounds on oxidative DNA damage in three ESSC cell lines  using a method similar to that previously described : see Metn = 30 total) were randomized into six groups: Normal group (n = 5): fed with water containing propylene glycol from the 1st week to 16th week, then fed only normal water for further 4 weeks (shaded in grey); 4-NQO group (n = 5): fed with water containing 4-NQO (100 μg/mL) from the 1st to 16th week (shaded in black) and maintained with regular drinking water for further 4 weeks; selenite group ; MSA group ; MSC group ; and Se-Met group : administered through force-feeding via intragastric intubation using 22-gauge needle size  [Six-week-old C57BL/6 mice were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd., Beijing, China . Five mice were maintained in each plastic cage in an air-conditioned room with a 12 h light/dark cycle. The temperature and relative humidity were kept at 25 °C ± 2 °C and 50 ± 10%, respectively. All mice were fed with a basal diet  and allowed free access to deionized water. All the animal procedures and experiments conducted in this study were approved by the Animal Ethics Committee of Shantou University Medical College (Permit NO. SUMC2021-228), and all efforts were made to minimize suffering to the animals. We used 4-Nitroquinoline 1-oxide (4-NQO) to induce esophageal lesions. Stock solution (1 mg/mL) was prepared weekly in propylene glycol, diluted in drinking water to a working concentration of 100 μg/mL, and stored at 4 °C. Drinking water containing 4-NQO was freshly prepared every week using deionized water and administered to the mice in light-shielded water bottles ,39,40. Tton, MA)  at a volAfter completing the experimental period (20 weeks), all mice were euthanatized with a 1% aqueous pentobarbital sodium solution (i p). The whole esophagus and stomach were opened longitudinally, and esophagus lesions were performed under white light and carefully identified. Tissues were fixed in freshly made 4% paraformaldehyde overnight at 4 °C, embedded in paraffin, and sectioned into 4 µm sections. A histopathologic assessment of esophagus sections was performed to examine the effects of Se compounds on the incidence of esophagus lesions. In addition to histologic evaluation, esophagus sections were immunostained for the proliferation marker Ki-67, oxidative DNA damage marker 8-OHdg, γ-H2AX, inflammatory marker CD45, CD4, and CD8, and tunnel assay. The selected dose was based on a previous study that showed the inhibitory effects of selenium compounds when tested on various types of cancer in vivo ,43,44.3) = (width2 × length)/2.Two certified pathologists conducted the histological determination of squamous neoplasia at the Shantou University Medical College on the sectioned tissue samples. The esophagus sections were de-paraffinized, rehydrated, stained with H & E for histopathology, and observed by a light microscope. The ESCC precursor lesions observed were classified into the following types: Squamous dysplasia—cytological atypia  and architectural . Low grade—involvement of only the lower half of the epithelium, with only mild cytological atypia. High grade—involvement of more than half of the epithelium or severe cytological atypia  according to WHO 2019 classification and reclassified as the same lesions using the binary classification system . Lesion Apoptosis was assayed by TUNEL staining using the Yeasen Biotech Kit according to the manufacturer’s instructions. Briefly, formalin-fixed, paraffin-embedded (FFPE) tissue on the slides was washed with PBS (pH 7.4) and permeabilized with 0.1% Triton X-100 for 2 min, followed by incubation with 50 μL of TUNEL reaction mixture in a humidified chamber at 37 °C for 1 h in the dark. Then, sections were counterstained with DAPI and observed under a fluorescence microscope . We calculated the percentage of TUNEL-positive cells by dividing the number of TUNEL-positive nuclei by the total number of DAPI-positive nuclei in defined fields and multiplied by 100.Immunostaining of esophagus sections for Ki-67, γ-H2AX, 8-OHdG, CD45, CD4, and CD8 was performed on formalin-fixed paraffin-embedded (FFPE) esophagus sections using the Envision technique, Dako Real EnVision Detection System, and Peroxidase/DAB+  according to the manufacturer’s protocol. See p value ≤ 0.05 was considered statistically significant; NS, non-significant.Statistical significance in the experiments was assessed using GraphPad Prism, version 8.02 . All data were collected and analyzed, blinded, and presented as mean ± SD. Statistical evaluations of the post hoc multiple group comparisons were conducted using one-way ANOVA and two-way ANOVA , followed by Tukey contrasts. A Based on our findings, we suggest that selenium possesses a robust chemotherapeutic effect against ESCC. This effect is related to promoting apoptosis, inhibiting the proliferation of cells, preventing oxidative stress, and reducing inflammatory T cells . Selenium could diminish high-grade dysplasia to low-grade dysplasia via multi-targeted effects, including anti-oxidants and anti-inflammatory effects . These d