Aim: Multiple myeloma (MM) is a hematological malignancy of antibody-producing mature B cells or plasma cells. The proteasome inhibitor, bortezomib, was the first-in-class compound to be FDA approved for MM and is frequently utilized in induction therapy. However, bortezomib refractory disease is a major clinical concern, and the efficacy of the pan-histone deacetylase inhibitor (HDACi), panobinostat, in bortezomib refractory disease indicates that HDAC targeting is a viable strategy. Here, we utilized isogenic bortezomib resistant models to profile HDAC expression and define baseline and HDACi-induced expression patterns of individual HDAC family members in sensitive vs. resistant cells to better understanding the potential for targeting these enzymes.Methods: Gene expression of HDAC family members in two sets of isogenic bortezomib sensitive or resistant myeloma cell lines was examined. These cell lines were subsequently treated with HDAC inhibitors: panobinostat or vorinostat, and HDAC expression was evaluated. CRISPR/Cas9 knockdown and pharmacological inhibition of specific HDAC family members were conducted.Results: Interestingly, HDAC6 and HDAC7 were significantly upregulated and downregulated, respectively, in bortezomib-resistant cells. Panobinostat was effective at inducing cell death in these lines and modulated HDAC expression in cell lines and patient samples. Knockdown of HDAC7 inhibited cell growth while pharmacologically inhibiting HDAC6 augmented cell death by panobinostat.Conclusion: Our data revealed heterogeneous expression of individual HDACs in bortezomib sensitive vs. resistant isogenic cell lines and patient samples treated with panobinostat. Cumulatively our findings highlight distinct roles for HDAC6 and HDAC7 in regulating cell death in the context of bortezomib resistance. Bortezomib, a proteasome inhibitor, is a cornerstone of anti-myeloma therapy and is frequently used as a component of frontline therapy-5. However, acquired or secondary resistance consistently emerges in patients who initially respond to bortezomib or other proteasome inhibitor-based therapies suggesting a role for epigenetic alterations as contributors to resistance. This concept was validated by the clinical efficacy of the histone deacetylase inhibitor (HDACi), panobinostat, which was approved by the FDA for the treatment of refractory and relapsed multiple myeloma-11. Broadly, HDACi represent a group of epigenetic agents that modify gene expression to restore normal differentiation and programmed cell death and have emerged as a novel class of anti-cancer drugs, especially in leukemia, lymphoma, and myeloma. HDACi regulate histone acetylation, a key epigenetic mark that influences gene expression, which is coordinately controlled by families of enzymes that are histone deacetylases (HDACs) and histone acetyltransferases, which in turn regulate various key cellular functions such as gene transcription, cell differentiation, cell cycle progression, and apoptosis.Multiple myeloma is an incurable clonal B-cell malignancy characterized by the accumulation of terminally differentiated, antibody-producing plasma cells in the bone marrow. HDAC6 is known to target several non-histone substrates like alpha-tubulin and HSP90 that control critical cellular functions, including protein degradation, trafficking, and folding. HDACi with selectivity for HDAC6 has been developed and explored as single agents or components of combination therapy strategies for multiple myeloma. HDAC7, a member of the HDAC IIa subfamily, differs from other HDACs because it has a long N terminal domain that enables HDAC7 to bind transcription factors and facilitates export to the cytoplasmic compartment in addition to its expected and conventional histone acetylation removal function,20. The N terminal domain has adaptor and phosphorylation domains in addition to the conventional C terminal catalytic domain. Decreased HDAC7 priming for cell death has been observed in neurons exposed to low potassium treatment, but not documented in myeloma. Interestingly both HDAC6 and 7 exert immune-modulatory effects in myeloma,23 but have not been specifically studied in the context of bortezomib refractory disease.Panobinostat is a pan-HDACi with the greatest potency against class I, II, and IV histone deacetylases. Class I , class II , and class IV (HDAC11) are zinc-dependent amidohydrolases that share the presence of a conserved deacetylase domain. Class II HDACs are further subdivided into class IIa  and class IIb (HDAC6 and 10). HDAC6, a class IIb HDAC subfamily member, is unique among family members by having two active catalytic domains and is expressed primarily in the cytoplasm,25; therefore, dosing/combination regimens that enable optimization of panobinostat’s efficacy without severe toxicities is clinically relevant. Recently the pivotal PANORAMA 3, an open-label, randomized, phase 2 study, demonstrated improved tolerability, particularly far less GI toxicity, by combining oral panobinostat with subcutaneous bortezomib plus oral dexamethasone while achieving similar efficacy as intravenously delivered bortezomib,26. However, panobinostat’s specific molecular mechanism of action is still largely unknown given its broad inhibitory effects on HDACs, which leaves the door open to further refine the strategy of targeting specific HDAC family members. This may further improve the toxicity profile of targeting HDACs while retaining anti-myeloma efficacy. This may be particularly true of class I HDACs, which have been shown to be targets of bortezomib-induced cytotoxicity. However, very few studies have examined specific HDAC family members in the context of bortezomib-containing regimens. Work by Kikuchi et al. reports that bortezomib causes downregulation of HDAC1, 2, and 3 at the transcriptional level and that overexpression of HDAC1 conferred resistance to bortezomib; however, HDAC expression in bortezomib-refractory models was not probed.The toxicity profile of panobinostat, which leads to poor tolerability, frequently limits its usage in combination with other commonly used agents treating multiple myelomaHere, we specifically examine bortezomib-sensitive and bortezomib-resistant isogenic myeloma cell lines to understand the potential for targeting specific HDAC family members and how HDAC expression is regulated by panobinostat exposure. We find heterogeneous expression of HDAC family members in bortezomib-sensitive and resistant lines. Interestingly, panobinostat treatment altered HDAC gene expression: HDAC7 was downregulated while HDAC6 was upregulated after panobinostat treatment in myeloma cell lines. This was also observed in patients treated with panobinostat. Knockdown of HDAC7 partially recapitulated panobinostat-induced cell death, and panobinostat synergized with HDAC6 selective inhibitors to induce cell death, highlighting potential strategies for more focused targeting of HDAC family members in bortezomib-refractory disease.,30. Resistant lines were then cultured in the presence of 10 nM bortezomib. Cell line identities were confirmed by Short Tandem Repeat DNA profiling as conducted by the MD Anderson Cancer Center Characterized Cell Line Core. All cell lines were cultured in RPMI1640  with 10% FBS , 1% L-glutamine , and 1% penicillin/streptomycin  at 37 °C in a 5% CO2 incubator. All cultures were free of bacterial, fungal, and mycoplasma contamination (mycoplasma contamination was tested every 6 months). The following drugs were used for the study: bortezomib, LC Laboratories, ; vorinostat, Cayman Chemical, ; panobinostat, LC Laboratories, ; ricolinostat, Selleck Chemicals, ; tubacin, Selleck Chemicals, .Multiple myeloma and lymphoma cell lines RPMI-8226, Kas6, Daudi, and SUDHL4, were from American Type Culture Collection . To generate bortezomib-refractory cells, parental RPMI-8226 or Kas6 cells (designated as RMPI-8226wt or Kas6wt) were chronically exposed to increasing concentrations of bortezomib to generate resistant lines (designated as RMPI-8226v10r or Kas6v10r). The actin gene was used as an internal control to normalize the amount of amplifiable RNA. The comparative CT method was used to determine relative gene expression for each target gene. Primers were synthesized by Sigma-Aldrich , and sequences are listed in Total RNA was isolated using RNeasy Mini Kit  from 3 million cells. Reverse transcription reaction was performed for each sample (1 μg of RNA) via iScript RT kit  per the manufacturer’s protocol. Real-time qPCR was carried out using the iTaq Universal SYBR Green PCR master mix  in a 20 μL total volume. The PCR conditions were described previously5) were plated in 12-well plates 24 h before drug treatment. After drug incubation, cell viability was measured by trypan blue exclusion assay using a Vi-CELL® . For analysis of DNA fragmentation, cells were harvested and pelleted by centrifugation. The pellets were then re-suspended in PBS containing 50 μg/mL propidium iodide (PI) , 0.1% Triton X-100 , and 0.1% sodium citrate . DNA PI staining was measured by fluorescence-activated cell-sorting analysis using the FL-3 channel . Cells displaying a hypodiploid DNA content that is indicative of DNA fragmentation were scored as apoptotic.Cells  with 1% Triton X-100 , 25 mM Tris , pH 7.5, 150 mM NaCl , and a protease inhibitor cocktail  for 1 h at 4 °C. Sample protein concentration was measured by Bradford assay . Lysates were boiled in a sample buffer containing 62.5 mmol/L Tris-HCl , 10% (w/v) glycerol , 100 mmol/L DTT , 2.3% SDS , and 0.002% bromophenol blue  for 5 min and cooled on ice for additional 5 min. Lysates were then subjected to SDS-PAGE at 110V for 1-1.5 h and subsequently transferred to PVDF membrane  at 100V for 1 h. The membranes were incubated in TBS blocking buffer containing 10 mmol/L Tris-HCl (pH 8.0), 150 mmol/L NaCl , and 5% nonfat milk  for 1 h at room temperature while shaking, and then rinsed once briefly with TBS-T containing 0.1% Tween-20 . The membranes were subsequently incubated with primary antibodies  diluted 1:1000 in blocking buffer overnight 4 °C, followed by TBS-T washing, and incubation with secondary antibodies  diluted 1:8000-1:10,000 in blocking buffer for 1 h at room temperature while shaking. Proteins were visualized with ECL , and densitometry was measured with NIH ImageJ .HDAC7 gene expression (5’-AAACCCCCTGGATGCACAGCCCCGGCG-3’) among the 6 gRNA. Afterward, cells with the above-mentioned gRNA were sorted as single cells in CoSTAR ultra-low cluster, 96-well plates , with conditioned media to allow single-cell cloning and expansion. This process was repeated once to identify sub-clones #1 and #2 with sufficient knockdown of HDAC7 gene expression.To knock out HDAC7 gene expression in RPMI-8226wt cells, we designed six guide RNAs (gRNAs) specific to a sequence in the HDAC7 region. The RMPI-8226wt cells were transiently electroporated with 240 ng of each gRNA mixed with 500 ng Invitrogen GeneArt™ Platinum™ Cas9 Nuclease  using the Invitrogen Neon Transfection System  at 1100 v, 30 ms, and 2 pulses. Subsequently, protein lysates harvested from cells with each of the six gRNAs were immunoblotted for HDAC7 to identify the gRNA that provided the most decrease of t-test or Mann Whitney test. Values were given as the mean ± SEM of triplicate or more. Statistical significance was set at P < 0.05. Synergy was calculated using isobologram analysis based on the Chou and Talalay method by Calcusyn software , with combination index (CI) values < 1 considered synergistic.Statistical analysis was performed using GraphPad Prism Software . As appropriate, raw data or percentage was compared by unpaired Student’s  and that HDAC1 overexpression conferred resistance to bortezomib whereas knockdown conferred sensitivity. These data prompted us to investigate the status of HDAC family members in models of established bortezomib resistance. Bortezomib-resistant cell lines were generated from two different human myeloma cell lines (RPMI-8226 and Kas6),30. These lines did not show mutations in the B5 subunit of the proteasome, as has been reported in patients with bortezomib refractory disease; however, increased activation of insulin-like growth factor receptor-1 (IGFR-1) due to autocrine and paracrine secretion of IGF1 has been cited as the mechanism of bortezomib resistance in these lines. In order to independently confirm the resistance of the lines, we treated cells with increasing doses of bortezomib and found that viability, as measured by trypan blue positivity, was significantly reduced in parental (RPMI-8226wt or Kas6wt) cells but not in resistant (RPMI-8226v10r or Kas6v10r) cells. As shown in vs. Kas6wt, with the difference in viability being significant upon exposure to 10, 50, or 100 nM bortezomib [Previous work has shown that bortezomib regulates the expression of HDAC family membersrtezomib . The senrtezomib  when norrtezomib .vs. wildtype cells [To facilitate comparison across the two different models of bortezomib resistance, we examined the expression of class II and IV HDAC family members individually. Both RPMI-8226v10r and Kas6v10r showed HDAC7 as the most down-regulated family member among class II and IV HDACs, compared to parental counterparts. In addition, we found that HDAC6 was upregulated in bortezomib-resistant myeloma cells pe cells ; howeverpe cells  and C.,14 and indicated reduced potency of vorinostat compared to panobinostat. To determine whether this reduced potency correlated with altered expression of class II and IV HDAC, we examined transcript levels after vorinostat and panobinostat treatment. Vorinostat exposure did not change the expression of HDAC4, 5, 6, 7, 9, 10, or 11. However, panobinostat significantly altered class II and IV expression among RPMI-8226 and Kas6 myeloma cells and correlated with the efficacy of panobinostat in these lines [Given the altered expression of HDAC family members between parental and bortezomib-resistant myeloma cells, we investigated whether pan-HDAC inhibition using vorinostat or panobinostat would induce differential responses. RPMI-8226 and Kas6 myeloma cells were treated with various concentrations of either vorinostat or panobinostat for 48 h. Neither RPMI-8226v10r nor Kas6v10r responded to vorinostat or panobinostat differently compared to wildtype RPMI-8226wt or Kas6wt, respectively , indicatse lines . The majse lines .We further examined HDAC7 expression before and after vorinostat or panobinostat treatment in wildtype and bortezomib-resistant myeloma cells individually. Because HDAC6 was increased in both RPMI-8226 and Kas6 resistant lines compared to parental lines , we hypoSince HDAC6 transcript and protein expressions were increased after exposure to panobinostat in sensitive and resistant myeloma cells, we hypothesized that HDAC6 specific inhibitors might augment panobinostat efficacy. Parental or bortezomib-resistant myeloma cells were treated with either ricolinostat or tubaicin, two distinct HDAC6-specific pharmacological inhibitors. We found that increasing concentrations of HDAC6 inhibitors decreased the cell viability of both parental and bortezomib-resistant RPMI-8226 and Kas6 cells . Adding . However, panobinostat’s documented efficacy is countered by toxicities, specifically gastrointestinal and cardiac issues,25. To maximize the efficacy of panobinostat and minimize undesired toxicity, we sought to understand the underlying mechanism of panobinostat from the perspective of targeting selective HDACs. Therefore, we employed isogenic bortezomib-resistant myeloma models to profile the expression of individual HDACs in sensitive versus resistant lines. Surprisingly, we discovered HDAC6 and HDAC7 were upregulated and downregulated, respectively, in two separate models of bortezomib-resistant myeloma cells. Furthermore, we demonstrated that treatment of these lines with panobinostat caused dysregulation of HDACs while vorinostat failed to do so, which suggested an association between HDACi potency and effects on altered expression of HDACs. In particular, panobinostat caused a substantial downregulation of HDAC7 as well as a significant upregulation of HDAC6 in myeloma cells. Similar observations were made in patients enrolled in a clinical trial using panobinostat as first-line therapy, although this conclusion is tempered by the small number of samples analyzed. These data have implications for mechanisms of bortezomib resistance as well as mechanisms of panobinostat activity in the setting of bortezomib resistance, and indicate that further study of these two HDACs may be a key to overcoming refractory multiple myeloma. However, we acknowledge that the underlying mechanism of bortezomib resistance is multifaceted and not limited to IGFR-1 activation. Our conclusion that individual HDACs are implicated in bortezomib resistance may not be generalizable because we model bortezomib resistance utilizing activation of IGFR-1 as an underlying mechanism in our cells, and we do not explore other mechanisms of bortezomib resistance. Our data showed that panobinostat decreased HDAC7 transcript and protein expression, and HDAC7 knockdown led to reduced growth and cell cycle redistribution towards a G1 population. Although we did not investigate the downstream targets of HDAC7 that may contribute to the decreased cell growth, HDAC7 regulates cyclin D1 expression in osteogenesis,32, and it is possible that this function of HDAC7 is conserved in myeloma. However, it has also been reported that HDAC7 promotes apoptosis in B acute lymphoblastic leukemia, which is contradictory to our findings. Therefore, we speculate that HDAC7 function is highly contextual and is dependent upon its presence in nuclei versus cytoplasm and its association with other proteins (including other HDACs such as HDAC3) in transcriptional complexes and the subsequent impact on gene expression.Panobinostat, a potent pan-HDACi, has been approved for refractory multiple myeloma and is the sole HDACi to show significant clinical benefit in this diseasein vitro data was further supported by the increase of HDAC6 in patient samples treated with panobinostat. HDAC6 is crucial in regulating protein degradation, response to endoplasmic reticular stress, and counteracts apoptosis induced by an overload of unfolded proteins. In bortezomib-refractory cells, we found that adding HDAC6 selective inhibitors to panobinostat further increased cell death. More importantly, the CI index analysis revealed that panobinostat synergized with HDAC6 selective inhibitors to enhance cell death. It has been reported that selective HDAC6 inhibitors augmented the anti-tumor activity of pomalidomide as well as bortezomib in myeloma. Our data revealed that HDAC6 inhibition also enhanced panobinostat efficacy, likely due to impaired protein degradation mechanism and increased ER stress. These data have implications for de-escalation of panobinostat when combined with HDAC6 inhibition, a strategy that may reduce the toxicities associated with the current dosing of panobinostat.Our data also revealed that panobinostat but not vorinostat upregulated HDAC6 expression in myeloma cells. The In summary, our data showed heterogeneous expression of HDACs between bortezomib-sensitive and resistant cells; however, HDAC7 downregulation in resistant lines was striking and consistent across models. A caveat of our study lies in the specific bortezomib refractory lines used. The cells were continuously cultured in bortezomib to maintain resistance. Also, both the resistant lines show increased activation of the IGFR-1, and we did not explore other mechanisms of bortezomib refractory disease to confirm if modulation of HDAC expression was universally conserved. Interestingly, panobinostat caused the further decrease of HDAC7 and increase of HDAC6, which was validated in patients treated with panobinostat. Using CRISPR, we reduced HDAC7 expression and found induction of cell cycle arrest and slowed cell growth. On the contrary, HDAC6 was upregulated by panobinostat, and pharmacological suppression of HDAC6 augmented cell death induced by panobinostat, highlighting an opportunity to combine HDAC inhibitors at low doses. Although we did not elaborate on this observation, our data in


ESR2), which also impacts inflammatory signaling of the colon. However, whether ERβ impacts the chromatin interaction (cistrome) of the main NFκB subunit p65 (RELA) is not known. We used p65 chromatin immunoprecipitation followed by sequencing (ChIP-Seq) in two different CRC cell lines, HT29 and SW480, with and without expression of ERβ. We here present the p65 colon cistrome of these two CRC cell lines. We identify that RELA and AP1 motifs are predominant in both cell lines, and additionally describe both common and cell line-specific p65 binding sites and correlate these to transcriptional changes related to inflammation, migration, apoptosis and circadian rhythm. Further, we determine that ERβ opposes a major fraction of p65 chromatin binding in HT29 cells, but enhances p65 binding in SW480 cells, thereby impacting the p65 cistrome differently in the two cell lines. However, the biological functions of the regulated genes appear to have similar roles in both cell lines. To our knowledge, this is the first time the p65 CRC cistrome is compared between different cell lines and the first time an influence by ERβ on the p65 cistrome is investigated. Our work provides a mechanistic foundation for a better understanding of how estrogen influences inflammatory signaling through NFκB in CRC cells.Inflammation is a primary component of both initiation and promotion of colorectal cancer (CRC). Cytokines secreted by macrophages, including tumor necrosis factor alpha (TNFα), activates the pro-survival transcription factor complex NFκB. The precise mechanism of NFκB in CRC is not well studied, but we recently reported the genome-wide transcriptional impact of TNFα in two CRC cell lines. Further, estrogen signaling influences inflammation in a complex manner and suppresses CRC development. CRC protective effects of estrogen have been shown to be mediated by estrogen receptor beta (ERβ,  Colorectal cancer (CRC) accounts for the third highest number of cancer deaths among both women and men in the Western world . Benign During inflammation, cytokines such as tumor necrosis factor alpha (TNFα) are released by macrophages. TNFα activates the nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB) transcription factor complex, which in turn induces several oncogenes and signaling pathways involved in tumor initiation and progression –7. ConstESR2) is present in epithelial colon and rectal cells  is upregulated in breast cancer, where it promotes cell proliferation and interacts with p65  and HT29 (RRID: CVCL_0320), previously generated to express ERβ and corresponding mock control cells , 30, 31,6 cells were used. Cells were treated with TNFα  Sigma-Aldrich) for 30 min and washed with PBS before cross-linking. Cells were first cross-linked with 2 mM disuccinimidyl glutarate (DSG)  for 45 min during shaking. After washing  to remove DSG, they were cross-linked again with formaldehyde (1%) for 10 min during shaking. The double crosslinking was used to capture both short- and long-range p65 chromatin interactions. Glycine  quenched the cross-linking reaction. After washing (twice with PBS), cells were collected and pelleted by centrifugation. Cell pellets were further processed at 4°C using ice cold reagents. After lysis in LB1  for 10 min, and centrifugation , pellets were suspended in LB2  for 5 min, centrifuged, and dissolved in LB3 buffer  to separate nuclear chromatin. Sonication generated 200-500 bp long fragments of chromatin. Following centrifugation , supernatants were collected in low-binding DNA tubes and incubated overnight with p65 antibody [Invitrogen, mouse monoclonal, cat no: 33-9900, lot no: QJ216251, RRID : AB_2533153, validated in  for Bioinformatics and Expression Analysis (BEA). DNA libraries were prepared using the NEB Next Ultra II DNA Library Prep Kit for Illumina (p/n NEB #E7645) and quality confirmed using TapeStation . Libraries were loaded (1.8 pM end concentration of 1%) and sequenced  using NextSeq 550 (Illumina).Spliced Transcripts Alignment to a Reference (STAR) was used to map unique ChIP-Seq reads to the human reference genome assembly hg38 (GRCh38) with the alignIntronMax flag set to 1. Peak calling was performed using Hypergeometric Optimization of Motif Enrichment (HOMER) over input with a four-fold enrichment as cutoff and applying a false discovery rate (FDR) less than 0.001. Peaks which overlapped within 200 bp and were present in at least two out of three biological replicates were used for downstream analysis. Raw tag counts were normalized using R and binding pattern differences were identified with edgeR package. To cluster and visualize the different peaks, Complex heatmap from R was used. Promoter regions were defined as -1kb to +100bp from TSS and genomic distribution of binding sites were identified by HOMER. Gene functional annotation was performed using Database for Annotation Visualization and Integrated Discovery (DAVID), with P <0.05 considered as significant.The p65 ChIP-Seq data is deposited in the Gene Expression Omnibus (GEO) repository (GSE160856), TNFα bead array gene expression data was published previously (available at GSE65979), and SW480ERβ input and HT29ERβ input controls (GSE149979).First, to understand the role of p65 transcriptional activity and oncogenic functions in CRC, we aimed to characterize its genome-wide binding in human CRC cells and correlate this to the TNFα-mediated transcriptional impact in the same cells. We used two well-characterized human colorectal adenocarcinoma cell lines: HT29 from a female primary tumor and SW480 from a male Dukes’ type B primary tumor.). We next used HOMER to determine DNA motifs of the identified peaks. As expected, we identified RELA as the top motif, followed by JUN-AP1, in both cell lines  procedure to capture long-range interactions of p65, we analyzed the chromatin bound by p65 in triplicate experiments of each cell line, HT29 and SW480. The sequencing produced between 24M and 65M (80%) of high-quality mapped reads per sample Table S1NFKBIB, NFKBIZ, TNFAIP3 (BCL3 (BIRC3 (NFκB2 (p52) and RELB, tumor suppressor p53, TNIP1, and CREB1 , and KCNH3, ). Pathway analysis of genes bound by p65 (-50kb to +2kb of TSS) revealed that genes with transcriptional regulatory functions (e.g. JUND), cell adhesion and migration , NFκB signaling, TNFα signaling, and apoptosis were enriched. This is in accordance with general NFκB functions  of genes . Other known targets were differently bound and regulated in HT29  and SW480  cells  transcriptome data set of the same cells . We foun1) cells Table S3To explore the extent that p65 binding is conserved between colon and breast cancer, we compared our generated p65 cistrome (colon) with previously published p65 ChIP-Seq data of the ER-positive breast cancer cell line MCF7. We selected a data set that also used double crosslinking . A heatmin vivo  TNFα-mediated upregulation of VEGFA, AGO2 and IGFL4. We thus identified that ERβ reduces a sizeable fraction of p65 binding, modifying TNFα regulation in HT29 cells, especially for genes involved in e.g. cell proliferation and cell-cell adhesion.We also compared the p65 ChIP-Seq data with corresponding TNFα gene expression data, with and without ERβ  remained. However, a high number (5796) of new p65 binding sites appeared in presence of ERβ .DUSP5 [which regulates inflammatory gene expression of TNFα . Among these, expression was attenuated in most (24), and enhanced in some (14). Genes suppressed by ERβ included BCL3, BIRC3, CCL20, NFκB2 and RELB  between the two cell lines, with and without ERβ Figure 7ll lines . OverallActivation of NFκB in the intestinal epithelia can lead to colitis-induced CRC . Our stuBMAL2, CLOCK). A previous study has shown that dysregulation of circadian rhythm increases the risk for colorectal cancer (CLOCK gene mutations have been identified in 53% of CRC with microsatellite instability (MSI)  in colon of HFD-fed mice  . Moreovety (MSI) . In breaty (MSI) , 53. In ty (MSI) , 55. In se model . We havefed mice . Here, iInterestingly, p65 chromatin binding appears relatively distinct between the two CRC cell lines, in support with the fine-tuned cell-specific manner whereby NFκB controls transcriptional regulation. The cell lines are indeed different in several respects. While both are derived from primary colon adenocarcinomas, the HT29 cell line is derived from a likely pre-menopausal (44-year-old) woman, whereas SW480 originates from a 50-year-old man , 58. We While the p65 binding pattern was similar between the two CRC cell lines, the p65 cistrome of breast cancer cell line MCF7 was more distinctly different. One of the well-known interaction-partner of p65 is the p53 protein . MCF7 ceWe have previously shown that TNFα triggers a transcriptional response in both CRC cell lines, and that ERβ modulates this . Here, wThe strength of this study includes the genome-wide approach to decrypt these interactions, which together with the validated high-quality ChIP-Seq data generates unbiased and reliable data. The significance of these findings is reinforced by the use of two different CRC cell lines and the comparison with transcriptional impact, as well as comparisons between our results and published data generated from cells of other origin. A shortcoming includes the use of exogenous expression of ERβ in the CRC cell lines. However, cell lines mostly lack endogenous expression of ERβ , 22. FurIn conclusion, we provide a mechanistic foundation for a better understanding of how estrogen influences inflammatory signaling through NFκB in CRC cells.The p65 ChIP-Seq data is deposited in the Gene Expression Omnibus (GEO) repository (GSE160856), TNFα bead array gene expression data was published previously (available at GSE65979), and SW480ERβ input and HT29ERβ input controls (GSE149979).CW contributed to conceptualization. Methodology performed by RI, LH, and AA. Validation done by RI and LH. Formal analysis was done by RI and LH. Curation, RI. RI and CW wrote the first original draft and all authors commented or edited. Visualization, RI. Supervision, CW and AA. Project administration, CW. All authors contributed to the article and approved the submitted version.National Cancer Institute at the National Institutes of Health (R01CA172437), the Swedish Cancer Society , Swedish Research Council (2017–01658), and Region Stockholm (HMT grant 20170804). RI was supported by a PhD student grant (KID) from the Karolinska Institutet.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The present Nigerian transmission network is faced with the difficulty of evacuating and dispatching reliable and quality electricity supply and simultaneously maintaining an operational standard of security to prevent any collapses. Therefore, this study developed a novel technique to optimize electrical current flow to provide in-depth research and analysis of current flowing in the transmission network circuit prone to danger during short-circuit faults. The research methodology involved the generation of unbalanced short-circuit calculations at every single node of the three-phase network using the symmetrical component method. Numerical simulation of different types of unbalanced short-circuit fault into the entire 330kV transmission network using unbalanced fault algorithms written in a flexible MATLAB program environment is also performed on every bus. The influence of these short-circuit faults is examined on the generated spectrum of line current magnitude. This study then generates a series of unbalanced current circuit and line losses analysis that unveils the different scenarios regarding existing network performance. The method adopted is promising. It established the most critical lines (about 20) with high unbalanced current magnitudes and high line losses during the disturbance. Based on the result analysis, four (quad) bundles of conductors is designed as a proposed modification to the upgrade of all critical double circuit lines and the conversion of single critical lines on the 330kV transmission network to improve the power transfer capability and also meet the future transmission network development plan. Furthermore, recommendations that are considered desirable in this study are proffered to ensure acceptable power quality and security in the network. Novel technique, optimize current, symmetrical component algorithm, Numerical simulation, line current spectrum, unbalanced current circuit, critical lines losses, Quad bundle parameter Therefore, it has become essential to operating energy delivered to transmission lines at maximum efficiency . Unfortu4Globally, many major blackouts caused by power system insecurity have been traced to fault on power lines. For example, the North American transmission system's interruption, occurring in 2003, interrupted supply for over 50 million people . The twoTherefore, this study provides in-depth knowledge of the flow of current in the network to solve the challenging problems inherent in designing the present and future power systems to deliver increasing electrical energy safely and in a sustainable economic manner. The more the power that flows through the power lines, the more will be the current that flows and consequently the power quality will decline. This study's uniqueness is in the novel technique developed to optimize the flow of electrical current, a significant quantity, in the network, which provides insight into the contingency analysis of the transmission lines' security dispatch operation. The approach involves the numerical simulation of various aspects of unbalance faults; single-line to the ground (SLG), line-line (LL), double line to ground (DLG) into each line of the three-phase network. The study's generated results showed that most of the lines (about 20) have high levels of unbalanced current magnitudes. The analysis covers all the 33 lines for the simulated 28 buses and categorized into four scenarios based on their characteristics, as revealed in this study, making it easy to determine and analyse the critical lines or weak areas with high losses. Further analysis of the result of the unbalanced current circuit and power line losses leads to the proposed reconductoring of quad bundles conductor design. Recommendations are made for the critical weak lines by supplying relevant information to improve the network's weak lines and future expansion planning.2The data collected from PHCN includes the 330-kV transmission network in Nigeria, with particular attention to the schematic diagram of the entire single-line diagram, line data, and bus data. The data employed in the analysis are generated by the simulation of different types of unbalanced short-circuit faults into the network using unbalanced fault algorithms written in a flexible MATLAB program environment at every bus to examine their effects line current. The systematic, theoretical analysis of the methods applied and principles associated with the study areas discussed.2.1In this study, the Nigerian power network is used as the test system. The one-line diagram of the existing 28 bus and thirty-three (33) branches of the 330-kV Nigerian power system is given in 2.2The power system in any electrical circuit is analysed by calculating the system voltages and/or currents under normal and abnormal scenarios . However2.31.Single Line to Ground Fault (SLGF) involves the positive sequence, negative sequence, and zero sequences. For a fault at bus K, a phase to ground, the symmetrical components of fault current are given in Eqs. The various unbalanced fault expressions are given in Eqs. 2.Line-to-Line Fault (LLF): involves two conductors exposed to each other through fault impedance3.Double line-to-ground fault (DLGF): with this fault type, two-line conductors or phases come in contact both with each other through an impedance The fault phase current isThe phase currents are obtained from Eq. (8)is the prefault phase voltage at bus i.Using the sequence network components of the fault current, the symmetrical components of the ith bus voltages during fault are obtained as presented in Eqs. The phase voltages during fault areThe symmetrical components of fault current in line i to j are given as presented in Eqs. 2.4The current dependent load model is used in which load changing is in direct proportion to current at constant voltage and constant power. Since current is required to flow in every branch of the network, the injection model of the current, shown in Therefore, The current flowing through the power line at any bus K is determined by Eq. (16)If Hence, the real and reactive components of bus current in terms power and voltage buses are respectively given asUsing Eqs. However, for this study, the line currents' results, obtained by using 2.5By consider a three-phase transmission line with fault at node k, the model of a simulated fault is as shown in Thus, the fault current is given by Because the system is complex, MATLAB software is employed to maintain the same computational flow chart. The MATLAB code starts by identifying the system input arguments in which variables are manly positive and zero sequence impedance, as presented in 3Various aspects of faulted bus simulations begin from Kainji bus one and end at Gombe bus twenty-eight for each of the 33-line currents are generated. Since the network is quite extensive, this paper only presents few samples of the faulted bus  showing simulations for each of the 33 branches and 28 bus lines current as presented in Tables 3.1It has been discovered from the literature that most of the system collapses were a result of unbalance current in the three-phase when a fault occurs. Tables 3.1.1A large number of balanced currents characterizes the lines under this category. They are not affected by the faults occurring at different test system locations, as shown in 3.1.2In this category, the unbalanced current circuit ranges from 10 to12 in number, is associated with a double circuit, as presented in 3.1.3These lines have a particular shared characteristic of a single circuit except line 21–22 (Afam-Alaoji) with double circuits. There are ten (10) lines in this category, having a significant unbalance current ranging from 18 to 21 in numbers. However, the five lines, i.e., 12–13 (Omotosho-Benin), 13–18 (Benin-Onitsha), 15–17 (Sapele Aladja), 16–17(Delta-Aladja), and 21–22 (Afam-Alaoji) from the eastern part will not trip on 330kV grid with any of these northern faulted buses, 26 (Kano), 27 (Jos) and 28 Gombe) as presented in 3.1.4The eleven (11) lines in this category are the worst in unbalanced current circuits on the 330kV grid. When a short circuit occurs, all the faulted 28 buses affect these lines. These are the most critical lines when a fault occurs because only the faulted bus 28 has a balanced current circuit in all the three phases of the different unbalanced faults, as shown in 3.2To achieve higher efficiency and stability in the system, it became necessary to unveil lines that experience high power loss in this study based on the result of the unbalanced current analysis. The results of all the line current magnitudes obtained  and double circuit (DC) on the network. A careful study of these critical lines showed that these lines need ‘upgrade’ or ‘conversion’ as the case may be. It should be noted here that most of the existing double circuits are double conductor bison. The proposed specifications required for the construction of quad bundle conductors are presented in Eqs. The resistance (RT) of the four-conductor bundle is calculated using On substituting, we have (for one conductor)Resistance (R) =0.01507 Ω/km for four bundle conductors.The Geometric Mean Radius (GMR) and GMD are given in Eqs. System of conductors is 14m while the bundle diameter for a four-bundle conductor arrangement is 64.6 cm. The radius of the camel conductor is 0,015075m.where:L) are calculated using Eqs. The Line Inductance (L) and Inductive Reactance :The line Susceptance is calculated using Thus, the generated electrical line parameters  times on fault between 6/5/2015 and 1/9/2017, which is clear evidence of inadequate protection relaying scheme. It should also be noted that these lines are connected to either the generator bus or Osogbo bus , or Benin bus , except Alaoji-Onitsha. Thus, these lines will collapse in the event of significant fault occurrence without adequate protection relaying scheme.•It is discovered from •Further investigation in the study revealed that additional lines are required from Shiroro, Benin, Omotosho substations, and the modification of these lines to form part of North West ting. A similar transformation can be implemented from Gombe, Kano, and a new substation (links Gombe) to form part of the North East ring.•A new substation should be introduced at Kangiwa , about 189 KM and 122 KM away from Kainji and Birnin Kebbi. It is worth mentioning here that line 1–2 (Kainji-Birnin Kebbi), a single circuit and long line that is not limited by stability limits, has the lowest magnitude level of the balanced current circuit as presented in •There is an urgent request to replace those identified critical lines with the newly designed specifications for quad bundle conductors, as shown in •The transmission grid may also need to be made more ‘intelligent’ through the configuration and training of Artificial Neural Network (ANN). That way, applying a set of line currents obtained from the numerical simulation of various aspects of faults  branches of the Nigerian 330kV transmission network when subjected to various aspects of asymmetrical faults at twenty-eight (28 buses) different locations. An ideal algorithm was developed for a set of unbalanced short-circuit calculations models of the network. It simulated the unbalanced short-circuit faults  into each line of three-phase networks. The novel approach was implemented to form the basis to develop a strategy that identified the network's different problem areas, such as current unbalance circuit, high line current magnitude and losses, and critical weak lines. Based on these findings, the lines revealed that enough provision was not provided to have a close loop in the system. The study moved further to explore calculation and design parameters for the critical lines that require urgent attention as a power grid strengthening strategy. The study unveiled the Nigerian 330kV national grid's terrible and unsatisfactory state and proffered recommendations that need modifications to promote better efficiency, reliability, and security in the power line network. It is evident from the study that the priory of the transmission line expansion plan is of more priority over an increase in generation capacity for the evacuation of the generated energy. The data generated in this study will help system expansion planning, utilities desirous of minimizing network losses, and policymakers wishing to formulate more effective policies.Ademola Abdulkareem: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Wrote the paper.A. Adesanya: Performed the experiments; Wrote the paper.A. F. Agbetuyi & A. S. Alayande: Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.10.13039/501100012497Covenant University Centre for Research, Innovation and Discovery.This work was supported by the Data will be made available on request.The authors declare no conflict of interest.No additional information is available for this paper.


Cell lines are widely used in research and for diagnostic tests and are often shared between laboratories. Lack of cell line authentication can result in the use of contaminated or misidentified cell lines, potentially affecting the results from research and diagnostic activities. Cell line authentication and contamination detection based on metagenomic high-throughput sequencing (HTS) was tested on DNA and RNA from 63 cell lines available at the Canadian Food Inspection Agency’s National Centre for Foreign Animal Disease. Through sequence comparison of the cytochrome c oxidase subunit 1 (COX1) gene, the species identity of 53 cell lines was confirmed, and eight cell lines were found to show a greater pairwise nucleotide identity in the COX1 sequence of a different species within the same expected genus. Two cell lines, LFBK-αvβ6 and SCP-HS, were determined to be composed of cells from a different species and genus. Mycoplasma contamination was not detected in any cell lines. However, several expected and unexpected viral sequences were detected, including part of the classical swine fever virus genome in the IB-RS-2 Clone D10 cell line. Metagenomics-based HTS is a useful laboratory QA tool for cell line authentication and contamination detection that should be conducted regularly. There have been reports where the cell line was misidentified by the source institute, rendering the results of any publication using that cell line questionable. For example, the KB cell line, believed to be oral or squamous cell carcinoma2, and the KU7 cell line believed to be derived from bladder cancer cells3, were both found to be HeLa cells. Vaughn et al.2 found 631 publications published between the years 2000–2014 that mentioned the use of the KB cell line, of which 574 articles were describing it incorrectly. These, and other papers describing misidentified cell lines, have been and may continue to be cited and used in other studies, thus potentially invalidating the research2. As an increasing number of cell lines are reported as being contaminated or misidentified, many scientific journals including Nature and PLOS ONE have now put policies in place for the authentication of cell lines used in their publications4. Two of the main causes of cell line misidentification are cross-contamination between cell lines and mislabeling of tubes or culture flasks4. Cross-contamination may occur within cell lines of the same species (intra-species cross-contamination) or between different species (inter-species cross-contamination). Cell lines may also be completely overgrown and replaced by a contaminating cell line5. Regularly confirming the identity of cell lines can prevent contamination and mislabeling errors from affecting future research and diagnostic test results.Cell line authentication is an essential part of ensuring the validity of research and diagnostic results. Misidentified or contaminated cell lines can present irreproducible or inaccurate results which may mislead future research1. As each human cell line has originated from a different individual, STR profiling allows for differentiation between them. For non-human cell lines, using genes such as the mitochondrial gene cytochrome c oxidase subunit I (COX1) for DNA barcoding may be used to determine the species of origin. Due to frequent third-position base substitutions in this gene there is a high rate of molecular evolution leading to diversification, which can even differentiate between various phylogeographic groups of the same species6. The species can then be determined by comparing the DNA barcode profile of a cell line to databases of these sequences 1. However, STR/SNP and COX 1-based methods do not provide information on the presence and type of microbial contamination.One of the methods used for cell line identification is short tandem repeat (STR) profiling, which has been widely used for human identification in forensicsShotgun metagenomic sequencing allows sequencing of a broader spectrum of DNA or RNA in a sample. Thus, it can be used for species identification of cell lines and potentially detect the presence of bacterial, viral, or fungal contamination. If specific STR and SNP loci are amplified prior to sequencing, STR/SNP profiling may be reliably implemented for the confirmation of the specific cell line. In this study, high-throughput sequencing (HTS) was performed on DNA and cDNA extracts from each of 63 cell lines available at the Canadian Food Inspection Agency (CFIA) National Centre of Foreign Animal Disease (NCFAD) to verify the species of origin and presence of microbial contamination.2, except for Trichoplusia ni cells which were grown with shaking at 27 °C for 24 h before collection. Adherent cell lines were dissociated using 0.25% Trypsin-0.1% EDTA, and cells in suspension were spun down at 4 °C for 10 min at a relative centrifugal force of 600, and re-suspended in culture media. An aliquot of cells was stained with 0.2% trypan blue and counted using a Cellometer Auto T4 counter (Nexcelom Bioscience).A total of 63 cell lines available at the NCFAD were seeded from frozen stocks and grown for 48 h at 37 °C and 5% CO6 viable cells using the manufacturer’s recommended protocol. The DNA and RNA were eluted into 50–100 μL of AE elution buffer (QIAGEN). Qubit dsDNA Broad Range (BR) and RNA High Sensitivity (HS) kits (Thermo Fisher Scientific) were used to quantify DNA and RNA in the extracts on the DS-11 FX fluorometer (Denovix).DNeasy Blood and Tissue kit (QIAGEN) was used to isolate DNA and RNA from ~ 2.5 × 10Invitrogen ezDNase enzyme (Thermo Fisher Scientific) was used for the digestion of cellular DNA within extracted nucleic acid prior to cDNA synthesis. Superscript IV First-Strand Synthesis module (Thermo Fisher Scientific) was used for the synthesis of the first strand of cDNA using a 1:1 ratio of random hexamers and oligo-dTs and 300 ng of RNA. The NEBNext Ultra II Second-Strand synthesis module (New England Biolabs) was used according to the manufacturer’s protocol to generate the second strand of cDNA. QIAQuick PCR purification kit (QIAGEN) was used to purify the double-stranded cDNA and eluted in EB buffer (QIAGEN) according to the manufacturer’s recommended protocol. The Qubit dsDNA BR kit (Thermo Fisher Scientific) was then used to quantify the cDNA using a DS11 FX fluorometer.Sequencing was performed separately on the DNA and cDNA samples with the cDNA samples separated into two runs including a test run with a smaller number of samples due to the timing of the availability of the samples Tables  and 2. LLibrary preparation for the cDNA samples was subsequently performed with the Nextera XT Library Prep kit (Illumina) following the manufacturer’s protocol due to a switch over of Illumina library preparation methods in the laboratory. In the first run, 26 samples were pooled and loaded at a final concentration of 10 pM with 1% PhiX, and sequencing was performed again on the Illumina MiSeq using a V2 flow cell with a 300-cycle (2 × 150 bp) cartridge. In the second run of cDNA samples, 65 samples were pooled at a final concentration of 18 pM with 1% PhiX, and sequencing was performed on a V3 flow cell with a 600-cycle (2 × 300 bp) cartridge.7 software . To determine the species of the cell line, metagenomic analysis was performed using the nf-villumina8 (v2.0.0) Nextflow9 workflow on the concatenated DNA and cDNA sequencing data. As part of the nf-villumina workflow, Illumina PhiX Sequencing Control V3 reads were removed using BBDuk10, and poor quality reads and adaptors were removed using fastp11. Taxonomic classification of the filtered reads was performed with Kraken 212 using an index of NCBI RefSeq sequences for bacteria, archaea, viruses and the GRCh38 human genome , and with Centrifuge using an index of NCBI nt sequences (downloaded and built 2020-02-04). Quality filtered reads were assembled into contigs with Megahit13, Shovill14, and Unicycler15, which were queried against the NCBI nt database  using nucleotide BLAST+17 (v2.11.0)  restricting the search to eukaryotic NCBI nt database entries (i.e. belonging to NCBI taxonomic ID (taxid) 2759). The processed reads for each cell line were mapped against the top matching COX1 sequence identified by BLAST analysis using Snippy (v4.6.0)18 as part of the nf-illmap Nextflow workflow (v1.0.0)19. The resulting BAM alignment file was loaded into Geneious v.9.1.820 where a threshold for coverage depth was set to a minimum of three, and variants were called using the Find Variations/SNPs tools with default settings except Minimum Coverage = 3 and Minimum Variant Frequency = 0.75. Variants were only called if the read depth had a minimum coverage of 3×. MDBK-HS-1 is from the cell lines available at CFIA NCFAD in Winnipeg, Manitoba, Canada while MDBK-HS-2 came from the CFIA NCAD laboratory in Lethbridge, Alberta, Canada. For cell lines where the observed species from the top BLAST match was not as expected based on laboratory records, the reads were additionally mapped to the CytB gene sequence using the same methods as was used for mapping to the COX1 sequences.iGenomX DNA sequencing reads were demultiplexed using the fgbio21. As part of DAMIAN analysis, raw sequencing reads were trimmed using Trimmomatic22 with default settings and assembled using SPAdes23. Contigs were taxonomically classified using nucleotide BLAST+ (v2.11.0) (DAMIAN BLAST+ option “progressive”) and the NCBI nt database . Trimmed reads were mapped to the viral genomes identified by DAMIAN and additional nucleotide BLAST analysis using the nf-illmap workflow. Variants were called in Geneious V.9.1.820 using the method described above.RNA and DNA viruses and bacteria were identified from the cell line DNA and cDNA sequencing data using DAMIANCOX1 gene of the top mitochondrial genome BLAST match for each cell line. All observed species in this list matched the species recorded in the institute’s cell line inventory list. This list also includes five archived cell lines that have been documented as “unknown” which did not have a defined species listed.Table 25; however, there were no BLAST results from the LFBK-αvβ6 de novo assembled contigs that corresponded to the Bos taurus genome or mitogenome. All BLAST results matched sequences from the Sus scrofa genome and mitogenome. Figure B. taurus and S. scrofa COX1 sequences. A total of 880 reads from LFBK-αvβ6 mapped to the S. scrofa COX1 gene and had a breadth of coverage of 100% with 0 total variants  between the mapped reads and the reference, while only 77 reads mapped to the B. taurus reference COX1 gene with a breadth of coverage of 44.1% and 98 total variants  than the expected species based on available documentation. For these samples, reads were mapped against the COX1 sequences from both the expected and observed species. This analysis showed that, when reads were mapped against a reference sequence representing the expected species, more variants were observed than when they were mapped against a reference representing the observed species, suggesting that the cell line is derived from a different species than was expected  sequence. While the Cytb sequences between the observed and expected species also share a high similarity , Table b analysis are consistent with those of the COX1 analysis suggesting with higher confidence that the cell lines are derived from a different species than expected.Eight cell lines  were found to align better to the ed Table . The COX26. Reads that were classified as classical swine fever virus (CSFV) were also found in the IB-RS-2 Clone D10 cell line with a 39.5% breadth of coverage across the viral genome with seven total variants relative to the reference genome. In the T. ni insect cell line, reads identified as Flock House virus had a breadth of coverage of 85.1% across the reference genome with two total variants  in CPAE, and the common porcine circovirus 1 (PCV1) in swine-derived PK-15 (PCV+) cells. Sequences matching these viruses were detected as expected, and PCV1 was also found in all four IPAM clones . Examining the polymorphic isoenzyme profiles between species for cell line confirmation has limitations including limited species range, low sensitivity of detection, and complex data interpretation.COX1 sequence that was consistent with the expected species; the reads from each of these cell lines had a breadth of coverage of > 95% across the COX1 gene, and no more than five variants compared to the reference. LFBK-αvβ6 and SCP-HS cells were found to be from a different genus than expected, suggesting that the cell lines had been misidentified, contaminated, or mislabeled. When reads from the LFBK-αvβ6 and SCP-HS cell lines were mapped to the COX1 genes corresponding to the species identified by BLAST analysis, no variants were observed in either sample. The porcine DNA found within the LFBK-αvβ6 cell line is consistent with a published erratum that this cell line is of porcine origin25. LFBK-αvβ6 isoenzyme patterns are also consistent with cultures of porcine origin (unpublished results).In this study, 53 of the 63 cell lines had a COX1 and Cytb genes were used as an indication of how similar the cell line was to a particular species. The difference in the number of variants between the expected and observed species varied for each cell line (between 9–64 variants for COX1 and 1–68 for CytB); however, in each case, the number of variants was higher when aligned to the expected species as compared to the observed species, except for PaLu and PaSPT where the reads mapped to the Cytb gene had a higher number of SNPs to the observed species than the expected. Turner et al.27 describes the morphological differences between species of the Chlorocebus genus of Old World monkeys, and reported that various geographical locations may permit deviation from the predicted morphology of these species. Thus, the species of the individual animal from which each of these cell lines originated was likely misidentified. It was also noticed that the number of variants in the bat cell lines (PaLu and PaSPT) was considerably higher in the observed species  compared to all of the other cell lines (6 or fewer variants). The genus Pteropus is known to be very diverse with a large number of species28, therefore, additional investigation will be required to determine if the cell lines are, in fact P. ornatus, as identified here, or if there was a misidentification between closely related species when the cell line was originally created.Assembled sequences from eight of the cell lines showed a higher pairwise nucleotide identity to a different species within the same genus than what was expected Table . Five of29, while non-human cell lines are best identified using DNA barcoding with the COX1 gene6. The International Cell Line Authentication Committee (ICLAC) keeps a Register of all known misidentified or cross-contaminated cell lines. As of this study, the Register was last updated March 25, 2020 and contains a total of 509 cell lines that are misidentified; of these only 38 were nonhuman cell lines30. This is likely not because human cell lines are more susceptible to contamination compared to nonhuman cell lines, but rather, because there is more information available for human cell lines in addition to the limitations of STR profiling which is only applicable for single species differentiation30. Thus, the method described here is useful since it can identify the species as well as the presence of contaminants such as other cell lines, mycoplasma, or viruses1.The current gold standard for the authentication of human cell lines is STR profilingmycoplasma contamination of cell lines. Depending on the species of mycoplasma, the effects on the cells vary from changes in protein and nucleic acid synthesis levels to a complete loss of the culture31. Detection of contamination is difficult, due in part to the small size (0.3–0.8 µM)32 of the mycoplasma cells, which allows them to pass through filters33. Additionally, high concentrations of mycoplasma are possible without any obvious visual signs33. In this study, mycoplasma was not detected in any of the 63 cell lines tested. This result was expected as the NCFAD currently has quality control procedures in place to check for mycoplasma contamination in their cultures, and the results here are consistent with the systems in place.Experimental results can be negatively impacted due to 34 and was present in the CPAE and OA3.Ts cell lines. Human adenovirus C was found in both HEK-293 and A549 cells. PCV1, a ubiquitous virus in pigs, was found as expected in the PK-15 (PCV +) cell line and in all four of the IPAM clones tested. Retroviral sequences are common in the genomes of their hosts due to insertion into the host genome25. The near-complete genome (99.3% breadth of coverage with 77 variants) of murine leukemia virus (MuLV) was detected in the P3X63-Ag8 cell line. Partial genomes from retroviruses such as avian leukosis virus (ALV) and porcine endogenous retrovirus (PERV) were detected in some cell lines.The presence of certain viruses was expected in some of the cell lines. Bovine viral diarrhea virus 2 (BVDV2) is a common contaminant in fetal bovine serum28, however, testing of this cell line obtained from the American Type Culture Collection (ATCC) by Bolin, et al.35 detected the virus in this clone. The presence of the entire CSFV genome was also found in the same cell line used by the Pirbright Institute, UK .Sequencing reads covering 39.5% of the CSFV genome were found in the cell line IB-RS-2 Clone D10 with seven total variants shared between the reads mapped and the reference genome. This clone was originally determined to be free of CSFV contaminationmycoplasma) or the presence of unexpected viruses.Cell line authentication is important for the reproducibility and accuracy of research and diagnostics involving cell lines as it can help identify unexpected errors and contamination in archived material and cell lines obtained from other sources. This study confirmed the species identity of 63 cell lines that are available at the Canadian Food Inspection Agency’s National Centre for Foreign Animal Disease. Of these cell lines, five were previously undefined, eight were determined to be derived from a different species within the same genus than was expected, and two were identified as species from different genera than expected. The methods described in this study or other comparable methods can be useful as they provide a single approach for species identification, as well as for the detection of contamination (e.g.,


Malignant pleural mesothelioma (MPM) is an aggressive malignancy with a severe prognosis, and with a long-standing need for more effective therapeutic approaches. However, treatment with immune checkpoint inhibitors is becoming an increasingly effective strategy for MPM patients. In this scenario, epigenetic modifications may negatively regulate the interplay between immune and malignant cells within the tumor microenvironment, thus contributing to the highly immunosuppressive contexture of MPM that may limit the efficacy of immunotherapy. Aiming to further improve prospectively the clinical efficacy of immunotherapeutic approaches in MPM, we investigated the immunomodulatory potential of different classes of epigenetic drugs  guadecitabine, histone deacetylase inhibitors VPA and SAHA, or EZH2 inhibitors EPZ-6438) in epithelioid, biphasic, and sarcomatoid MPM cell lines, by cytofluorimetric and real-time PCR analyses. We also characterized the effects of the DHA, guadecitabine, on the gene expression profiles (GEP) of the investigated MPM cell lines by the nCounter platform. Among investigated drugs, exposure of MPM cells to guadecitabine, either alone or in combination with VPA, SAHA and EPZ-6438 demonstrated to be the main driver of the induction/upregulation of immune molecules functionally crucial in host-tumor interaction  in all three MPM subtypes investigated. Additionally, GEP demonstrated that treatment with guadecitabine led to the activation of genes involved in several immune-related functional classes mainly in the sarcomatoid subtype. Furthermore, among investigated MPM subtypes, DHA-induced CDH1 expression that contributes to restoring the epithelial phenotype was highest in sarcomatoid cells. Altogether, our results contribute to providing the rationale to develop new epigenetically-based immunotherapeutic approaches for MPM patients, potentially tailored to the specific histologic subtypes. Malignant pleural mesothelioma (MPM) is a low-frequency thoracic neoplasm arising from mesothelial cells of the pleural cavity, featuring a high aggressiveness  . The proDespite the accumulation of novel insights about MPM biology ,11 and tEpigenetic modifications include principally DNA methylation, post-translational modifications (PTMs) of histone proteins, chromatin remodeling components, histone variant exchange, and non-coding RNAs ,22. UnliOther epigenetic compounds have been demonstrated to modulate immune cell transcriptional programs. Tazemetostat (EPZ-6438), an inhibitor of the enhancer of zeste homologue 2 (EZH2i) favored chemokine-dependent T cell attraction as a consequence of enhanced expression of the immunostimulatory molecules in cancer . FurtherBased on the encouraging sensitivity of MPM to immunotherapy and on the promising immunomodulatory effects of epigenetic remodeling, this study focused to compare the properties of different classes of epigenetic drugs, including agents recently used in clinical trials , on MPM cell lines belonging to the three main subtypes. The identification of guadecitabine as the main driver of the greatest immunomodulatory effects led us to expand the characterization of the DHA activity by analyzing changes in gene expression profiles (GEP) of MPM cell lines belonging to the three subtypes and elucidating the biologic functions of genes representing the expression signature of epigenetically-treated vs. untreated MPM cells. Results obtained provide the rationale for the development of new more effective epigenetic-based immunotherapeutic strategies for the treatment of MPM patients also relating to their histologic prognosis.p ≤ 0.05) in 4/5  treated cell lines, as compared to untreated cells  in 4/5  treated cell lines, as compared to untreated cells  up-regulated the expression in the two constitutively positive sarcomatoid cell lines  induced by the different investigated epigenetic drugs alone or in combinations, in 5 MPM cell lines. Baseline levels of NY-ESO-1 and MAGE-A1 were negative in five and two (one epithelioid and one biphasic) cell lines, respectively; all cell lines were constitutively positive for MAGE-A3 expression. A de novo expression of NY-ESO-1 was induced by guadecitabine and guadecitabine-based combinations in 5/5 MPM cell lines . No indull lines . No indull lines . Finallyll lines . No signll lines .p ≤ 0.05) up-regulation of CDH1 expression was observed in 1 (epithelioid)/3 CDH1-positive cell lines after guadecitabine and guadecitabine-combined treatments, and in one biphasic cell line treated with VPA or guadecitabine plus VPA. Other treatments did not induce any modulation of CDH1 expression in investigated cell lines  genes were differentially  expressed in treated vs. untreated cells. Mean of 68.3% (range: 46.7–83.7%) and 31.7% (range: 16.3–53.3%) DEG were respectively up-regulated (FC ≥ 0.58) and downregulated (FC ≤ −0.58), in the 10 investigated MPM cell lines, by treatment.According to Ingenuity Pathway Analysis (IPA), 248 canonical pathways were modulated (Z-score ≥ 2 or Z-score ≤ −2) in treated compared to untreated cells, in at least one cell line . Among tIPA upstream regulator analysis identified 660 upstream regulators responsible for changes in the expression profiles of at least one MPM cell line after guadecitabine treatment . Among tStemming from these results, we performed a subtype-specific investigation of the modulation of functional classes of immune-related genes, after guadecitabine treatment.A strongly upregulated expression of multiple CTA genes was observed in all the three DHA-treated subtypes . Comprehp < 0.001) was proved between changes  induced by guadecitabine in the constitutive levels of investigated genes expression, measured by quantitative real-time PCR or by nCounter multiplex gene expression analysis in the 10 MPM cell lines  ligand CD74, which represents an independent prognostic factor of survival for MPM patients, whatever the histological subtype, being, however, more expressed in the epithelial type; indeed, its low tumoral expression was associated with dismal prognosis . Some stAlthough the number of investigated MPM cell lines was limited, the sensitivity to epigenetic drugs treatment, heterogeneously observed among MPM cell lines belonging to the three different subtypes, was more evident in the most aggressive sarcomatoid MPM subtype, supporting the need to develop personalized combination therapies to render these aggressive tumors more responsive to immunotherapy.Comprehensively these studies laid the groundwork for planning further in vivo studies to demonstrate the potential of guadecitabine-based immunotherapeutic strategies for MPM treatment, considering also the influence of MPM subtypes in the epigenetic drugs’ sensitivity.Ten MPM cell lines were selected in order to represent the three main subtypes: the epithelioid Meso1 and Meso6, the biphasic Meso4, Meso5, Meso7 and Meso13, and the sarcomatoid Meso2, Meso3, Meso8 and Meso11. All cell lines were established by our group from pleural effusions of MPM patients deal with in the University Hospital of Siena, under approval by the Committee on Human Research. All cell lines were cultured in HAM’s F-12 medium  supplemented with 10% heat-inactivated fetal bovine serum , 2 mML-glutamine, and 100 µg/µL of penicillin/streptomycin .PE mouse anti-human ICAM-1 clone 84H10 monoclonal antibody (mAb) was purchased from Beckman Coulter and alexafluor 488 mouse anti-human HLA-ABC (class I) clone W6/32 mAb was purchased from Biolegend. Guadecitabine was purchased from MedChemExpress LLC ; HDAC inhibitors, VPA and SAHA, were purchased from Sigma Aldrich Corporation  and Cayman Chemical , respectively and the EZH2i EPZ-6438 was purchased from Selleck Chemicals .6/13 mL of complete medium (day 0) and treated with 1 µM guadecitabine . Correlation between mFC in the expression of selected genes, measured by nCounter assay and quantitative real-time PCR analyses, was evaluated by Pearson’s correlation coefficient (r).Statistical analyses were carried out by GraphPad Prism 7.05 .


Pseudomonas aeruginosa in comparison to the host-niche-adapted Salmonella enterica. We demonstrate that P. aeruginosa, but not S. enterica, hypermutators evolve toward higher fitness under planktonic conditions. Adaptation to increased growth performance was accompanied by a reversible perturbing of the local genetic context of membrane and cell wall biosynthesis genes. Furthermore, we observed a fine-tuning of complex regulatory circuits involving multiple di-guanylate modulating enzymes that regulate the transition between fast growing planktonic and sessile biofilm-associated lifestyles. The redundancy and local specificity of the di-guanylate signaling pathways seem to allow a convergent shift toward increased growth performance across niche-adapted clonal P. aeruginosa lineages, which is accompanied by a pronounced heterogeneity of their motility, virulence, and biofilm phenotypes.Identifying genetic factors that contribute to the evolution of adaptive phenotypes in pathogenic bacteria is key to understanding the establishment of infectious diseases. In this study, we performed mutation accumulation experiments to record the frequency of mutations and their effect on fitness in hypermutator strains of the environmental bacterium  Pseudomonas aeruginosa is an environmental generalist and an opportunistic pathogen capable of infecting a wide variety of hosts ranging from plants to humans [o humans , 2. Morpo humans . Phenotyo humans , mediateo humans –8, rearro humans –11 or byo humans .P. aeruginosa strains are large (5–7 Mbp) and encode a variety of regulatory circuits. These provide a remarkable phenotypic plasticity and a high adaptation potential to the opportunistic pathogen. For the successful colonizing of new habitats, P. aeruginosa must maintain this adaptation potential even under constant conditions. However, as it has been observed for various bacteria and yeasts, constant conditions favor the genetic selection of niche specialists, which have a higher fitness, but show fitness decay in other environments [The genomes of ronments . The traronments –18.P. aeruginosa and recorded the type and frequency of mutations as well as their effect on bacterial fitness as compared to S. enterica. We used DNA repair-deficient bacterial strains characterized with ~100 times higher mutation rates in order to accelerate MA. Each of the species was continuously cultivated in the exponential phase under weak and strong bottlenecking conditions. In the context of experimental evolution, strong bottlenecking and a lower size of the effective population are thought to promote fixation of random mutations and, since most mutations are deleterious, lead to a loss of fitness. Conversely, weak bottlenecking enables natural selection and is more favorable to the fixation of beneficial and elimination of harmful mutations [P. aeruginosa, but not S. enterica hypermutator strains adapt to planktonic rich medium conditions by evolving increased growth performance. We show that the increase in fitness in P. aeruginosa was associated with an increased rate of phase variation events in the promoter regions of genes involved in membrane and cell wall biogenesis. Furthermore, the fine-tuning of cyclic di-guanylate (c-di-GMP) signaling-governed pathways was observed, indicating that P. aeruginosa adapts to lifestyles between planktonic and biofilm growth modes.In this study, we performed mutation accumulation (MA) experiments in the environmental bacterium utations , 20. Of P. aeruginosa and S. enterica were taken from a PA14 transposon insertion library [mutS gene was replaced with an Frt-Kanamycin-Frt cassette in the S. enterica serovar Typhimurium LT2 background), respectively. Bacterial cultures were grown in 96-well plates with continuous shaking at 180 rpm. To synchronize the growth of the studied species, P. aeruginosa and S. enterica cultures were grown at 37 °C in LB medium  and at 30 °C in LB medium supplemented with 0.2% glucose, respectively  and weak bottleneck (WBN) cultures were diluted to 1 and 100 cells per 100 μl, respectively, and S. enterica cultures were diluted to 1 (SBN) and 250 (WBN) cells per 100 μl (see Supplementary Note SStarting cell lines of https://www.python.org/). The sequencing coverage was analyzed using SAMtools and was determined to be on average 32×. After quality filtering of specific nucleotide variations, mutations were checked using Integrative Genomics Viewer (v.2.3.98) [For whole-genome sequencing, genomic DNA was isolated from, in total, 83 planktonic overnight cultures using the DNeasy Blood & Tissue kit  and fragmented using the S2/E210 Focused-ultrasonicator  to achieve 400-nt-long fragments. Libraries were prepared using the NEBNext Ultra DNA Library Prep Kit for Illumina  according to the manufacturer’s instructions. The libraries were sequenced using Illumina MiSeq (2 × 250-bp paired-ended reads). Reads were mapped to PA14 reference genome using Burrow–Wheeler Aligner , re-mapphttps://www.perl.org/) and C shell scripts. Differential gene expression was estimated with the help of custom R scripts utilizing DESeq2 [RNA sequencing was performed for three randomly selected clonal isolates from each WBN cell line. RNA was extracted from the logarithmic stage cultures of the selected clones and further processed as described in the protocol in Supplementary Note Sg DESeq2 , tidyverGalleria mellonella (greater wax moth) infection model [Fitness was analyzed by determining the optical density of the cultures throughout the growth phase. Swimming assays were performed as previously described . Virulenon model . Biofilmon model , 30. In on model . The detP. aeruginosa mutant through defined weak bottlenecks (WBNs) in standard laboratory conditions  measurements demonstrated that evolved P. aeruginosa WBN clones developed a shortened lag phase   rates in P. aeruginosa, no differences in nucleotide substitution rates between WBN and SBN cell lines in either of the species were detected, indicating that there was no clear selection pattern for SNPs in the various bottlenecking conditions of our MA experiment.To identify mutation patterns that reflect the st) Fig. . Among tS. enterica WBN and SBN cell lines, and the rate of intragenic indels in P. aeruginosa WBN cell lines was comparable to that of the S. enterica WBN cell lines. However, the rate of intragenic indels in P. aeruginosa SBN cell lines was ~50% higher as compared to the P. aeruginosa WBN cell lines   Fig. . IntrageP. aeruginosa as compared to S. enterica (p < 0.001 for WBN cell lines and p = 0.09 (nonsignificant) in SBN cell lines, Mann–Whitney test). Interestingly, we found an enrichment in intergenic indels that preceded genes of the functional COG category “cell wall/membrane/envelope biogenesis”  exclusively in the P. aeruginosa WBN cell lines, indicating that there was a positive selection for the respective indels.In the intergenic regions, the rate of indels did not differ between WBN and SBN cell lines of the same species Fig. . HoweverP. aeruginosa WBN clones, we re-analyzed the previously recorded genome sequences of 414 P. aeruginosa clinical isolates [P. aeruginosa indels that were exclusively found in WBN cell lines were also found in at least one and up to 213 clinical isolates. At the same time only 9 out of 22 indels that recorded exclusively in upstream gene regions in P. aeruginosa SBN cell lines were found in at least one clinical isolate. The significantly higher rate of intragenic WBN indels that were found in the clinical isolates  implies that the intergenic indels in the P. aeruginosa WBN cell lines are subject to positive selection also in P. aeruginosa clinical isolates, probably, due to their effect on the transcription and/or translation of downstream genes. Since a majority of the indels are within homopolymeric tracts, phase variation might facilitate adaptation to rapidly varying environments without the requirement for random mutations.To further confirm that the indels in the intergenic homopolymeric tracts are under positive selection in the isolates . Thirty P. aeruginosa WBN clones are translated into fitness changes, we randomly selected three isolates from each of the five WBN cell lines and compared the gene expression profile of these 15 evolved WBN clones with that of the starting cell line  genes, including PA14_14330 (spcS ortholog), exoY, pscBCDE, exsABC, PA14_42380 (exsD ortholog), PA14_42410 (exsE ortholog), popDBN, pcrDGHRV, pcr1-4 orthologs, pscNOPQRTU, and PA14_42630. The rsmZ/rsmY-downregulating clones also showed lower expression of type-VI secretion system (T6SS) genes , fha1, hsiB1, hsiC1, hcp1, clpV1) , PA14_20760 (cheR ortholog), and chemotaxis transducers PA14_28050, PA14_58650, PA14_61300, and PA14_67010) , PA14_64050 (pleD ortholog), and PA14_56280 (sadC ortholog)) were found in two thirds of the clones (9 out of 15). Changes in expression of rsmZ, rsmY, and genes encoding T3SS, T6SS, and di-guanylate cyclases are well known to be linked to the switch between motile and sessile lifestyles [To obtain a deeper understanding of how the genetic changes in the ne Table . The expfestyles –43. ThisWe observed a high variation in swimming motility between individual WBN clones Fig. . Their pG. mellonella model, showed extreme variability with phenotypes ranging from almost avirulent to more virulent than the starting cell line , which ulations , 48. A bP. aeruginosa strain evolved higher fitness in LB through a multitude of different pathways related to membrane biogenesis and fine-tuning of the balance between fast growing planktonic and sessile biofilm-associated lifestyles. We speculate that phase variation due to indels in intergenic homopolymeric tracts and adaptive changes engaging complex regulatory circuits with highly redundant c-di-GMP metabolic enzymes act in synergy, allowing P. aeruginosa to produce phenotypic diversity, maintain high versatility, and efficiently colonize new habitats.In conclusion, we demonstrated that the WBN clones of the hypermutator Supplemental MaterialTable S1


However, the molecular and cellular pathways by which α-klotho mediates these neuroprotective functions have yet to be fully elucidated. Key questions remain unanswered: which form of α-klotho  mediates its cognitive enhancing properties; what is the neuronal receptor for α-klotho and which signalling pathways are activated by α-klotho in the brain to enhance cognition; how does peripherally administered α-klotho mediate neuroprotection; and what is the molecular basis for the beneficial effect of the VS variant of α-klotho? In this review, we summarise the recent research on neuronal α-klotho and discuss how the neuroprotective properties of α-klotho could be exploited to tackle age- and neurodegeneration-associated cognitive dysfunction.Cognitive dysfunction is a key symptom of ageing and neurodegenerative disorders, such as Alzheimer’s disease (AD). Strategies to enhance cognition would impact the quality of life for a significant proportion of the ageing population. The α-klotho protein may protect against cognitive decline through multiple mechanisms: such as promoting optimal synaptic function via activation of N-methyl- IKL-VS homozygosity is associated with a reduced lifespan ,54 and dklotho SNP G395A is located in the promoter region and confers a higher affinity for transcription factors compared with wildtype, so was hypothesised to be a functional variant [The  variant . The G39 variant . The MMS variant . These dklotho gene have shed light on the neuroprotective properties of klotho and, when crossed with mouse models of neurodegenerative diseases, have highlighted the potential beneficial effect arising from enhancing klotho expression in such disorders (summarised in d-aspartate (NMDA) receptor subunit GluN2B [Despite the lack of information regarding the cell surface receptors and signalling pathways for klotho in the brain, studies with transgenic mice overexpressing the t GluN2B . Klotho-t GluN2B . Klotho t GluN2B . In wildt GluN2B . Viral et GluN2B . When klt GluN2B . In the t GluN2B .Oxidative stress has long been implicated in ageing-related cognitive impairment in both old experimental animals and aged humans . For exain vivo.In APP/PS1 mice intracerebral overexpression of full-length klotho cDNA by lentivirus injection ameliorated amyloid-β burden, neuronal and synaptic loss, and the cognitive deficits observed in this model of AD . The kloklotho expression throughout the body, so it is not clear whether the effects observed are due to increasing klotho in the CNS or the periphery. Targeted viral vector administration of klotho to discrete regions in the CNS has shown that klotho has direct beneficial actions on cells in the brain [Notwithstanding the limited knowledge of how klotho mediates neuroprotection and cognitive enhancement, the above observations  mediates its cognitive enhancing properties? Can the different forms substitute each other? What is the identity of the receptor(s) in the brain for the soluble and secreted forms of klotho and which signalling pathway(s) is activated by them in the brain to enhance cognition? What is the molecular basis for the beneficial effect of the heterozygous VS variant of klotho? Is it a gain of function, a loss of function or both? Given that KL-VS homozygosity appears to be detrimental, would too much klotho or overstimulation of its signalling pathways have toxic effects or be counterproductive to enhancing cognition? How does peripherally administered klotho mediate neuroprotection? Does it cross the BBB or act on non-neuronal cells in the neurovascular unit? Once more details are uncovered on the molecular and cellular mechanisms of action of the soluble and secreted forms of klotho in the brain, more targeted approaches to mimic the actions of klotho may be realised which will enable us to exploit its neuroprotective properties to tackle age- and neurodegeneration-associated cognitive dysfunction.


Furthermore, the resistance of ABCB1-overexpressing cells to palbociclib was reversed by 3 μM of the ABCB1 inhibitor, verapamil. Moreover, the incubation of ABCB1-overexpressing KB-C2 and SW620/Ad300 cells with up to 5 μM of palbociclib for 72 h, significantly upregulated the protein expression of ABCB1. The incubation with 3 µM of palbociclib for 2h significantly increased the intracellular accumulation of [3H]-paclitaxel, a substrate of ABCB1, in ABCB1 overexpressing KB-C2 cells but not in the corresponding non-resistant parental KB-3-1 cell line. However, the incubation of KB-C2 cells with 3 μM of palbociclib for 72 h decreased the intracellular accumulation of [3H]-paclitaxel due to an increase in the expression of the ABCB1 protein. Palbociclib produced a concentration-dependent increase in the basal ATPase activity of the ABCB1 transporter (EC50 = 4.73 μM). Molecular docking data indicated that palbociclib had a high binding affinity for the ABCB1 transporter at the substrate binding site, suggesting that palbociclib may compete with other ABCB1 substrates for the substrate binding site of the ABCB1. Overall, our results indicate that palbociclib is a substrate for the ABCB1 transporter and that its in vitro anticancer efficacy is significantly decreased in cancer cells overexpressing the ABCB1.Palbociclib was approved by the United States Food and Drug Administration for use, in combination with letrozole, as a first-line treatment for estrogen receptor-positive/human epidermal growth factor receptor 2-negative (ER+/HER2-) postmenopausal metastatic breast cancer. However, recent studies show that palbociclib may be an inhibitor of the ABCB1 transporter, although this remains to be elucidated. Therefore, we conducted experiments to determine the interaction of palbociclib with the ABCB1 transporter. Our  Recently, it was reported that some TKIs, such as GS-9973, and sitravatinib, inhibit the efflux function of ABCB1, thereby reversing, reversing drug resistance (Multidrug resistance (MDR) in tumors is defined as the development of resistance to structurally and mechanistically unrelated classes of anticancer drugs . MDR is sistance . Similarsistance . In contsistance . HoweverINK4A pathway is a key regulatory pathway in the transition from G1 to S phase (It is well known that unregulated cell division can lead to the development and progression of cancer . Cyclin- S phase . The dys S phase . CDK4/6  S phase  and the  S phase . The CDK S phase . The inh S phase . A recen S phase . Another S phase . Althoug S phase .ABCB1 and ABCG2-transfected Madin-Darby canine kidney II (MDCKII) cell lines, palbociclib was a substrate for the ABCB1 and ABCG2 transporters , mitoxantrone, and verapamil were purchased from Sigma Aldrich Trading Co. . All of the drugs were dissolved in 100% DMSO to produce a 10 mM stock solution.ABCB1 transporter was knocked out using the CRISPR/Cas9 system .The efficacy of palbociclib was determined using the MTT assay, which assesses cytotoxicity, as previously described . Briefly3VO4. Subsequently, the cells were incubated with vehicle (DMSO) or 0.1–20 μM of palbociclib for 3 min at 37°C. Subsequently, 5 mM of Mg2+ATP was added to activate ATP hydrolysis, and 20 min later, the reaction was terminated by adding 0.1 ml of a 5% sodium dodecyl sulfate solution. The inorganic phosphate produced by the activation of the ATPase was measured as previously described  was used to determine the effect of palbociclib on basal ABCB1 ATPase activity, as previously described . Brieflyescribed . In a se3H]-paclitaxel in the KB-3-1 parental and KB-C2 resistant cell lines was used to determine the effect of palbociclib on ABCB1-mediated drug efflux activity, following the same protocol as previously described  of at least three independent experiments. All data were expressed as mean ± SD and statistically analyzed using a one-way analysis of variance (ANOVA), followed by Tukey’s post hoc test. GraphPad Prism 8.1 software was used in to plot the graphs and analyze the data. The a priori significance levels were p < 0.05.All experiments were repeated at least three times and ICIn order to ascertain if palbociclib is a substrate for the ABCB1 transporter, we determined the efficacy of palbociclib in the ABCB1 overexpressing cell lines, KB-C2, SW620/Ad300, and HEK293/ABCB1, using the MTT assay.50 = 22.573 μM), SW620/Ad300 (IC50 = 9.045 μM), and HEK293/ABCB1 (IC50 = 13.855 μM) cells and their parental cell lines, KB-3-1 (IC50 = 5.014 μM), SW620 (IC50 = 3.921 μM), and HEK293/pcDNA3.1 (IC50 = 4.071 μM), respectively.As shown in ABCB1 knockout SW620 cells (RF = 1.16). In contrast, the efficacy of palbociclib was increased in SW620/Ad300 cells that did not have the gene for the ABCB1 transporter (RF = 1.23), compared to the non-modified SW620/Ad300 cells (RF = 2.31). These results indicated that knocking out the ABCB1 transporter gene increased the efficacy of palbociclib in the drug-resistant SW620/Ad300 cells to a magnitude similar to that of the parental SW620 cells. Overall, the above results indicated that the efficacy of palbociclib was significantly decreased in drug-resistant cells overexpressing the ABCB1 transporter.As shown in 50 = 5.258 μM) and HEK293/ABCG2-WT (IC50 = 4.644 μM) cells overexpressing the ABCG2 transporter and their parental cell lines, NCI-H460 (IC50 = 5.598 μM), and HEK293/pcDNA3.1 (IC50 = 4.071 μM), respectively.In order to ascertain if palbociclib was a substrate for the ABCG2 transporter, we determined the efficacy of palbociclib in the ABCG2 overexpressing cell lines, NCI-H460/MX20 and HEK293/ABCG2-WT. Palbociclib was cytotoxic in NCI-H460/MX20 (ICAs shown in ABCB1), palbociclib resistance was significantly decreased by 3 μM of verapamil .As shown in d to 0 h . This ef3H]-paclitaxel, compared to KB-C2 cells incubated with only palbociclib  of ABCB1 protein was performed. A docking simulation of palbociclib with paclitaxel-bound ABCB1 protein model (6QEX) was performed. The results showed that palbociclib has multiple interactions with the substrate binding site for the ABCB1 protein and an affinity score of -9.616 kcal/mol . PalbociNumerous studies have shown that the overexpression of the ABC transporters, ABCB1 and ABCG2, in certain types of solid tumors and leukemia, produce acquired drug resistance and attenuate, as well as abrogate, the efficacy of anticancer drugs with different chemical structures and mechanisms of action . It has 50 values, in the drug-selected cancer cell lines, KB-C2 and SW620/Ad300, which overexpress the ABCB1 transporter, compared to the drug-sensitive parental cancer cell lines, KB-3-1 and SW620, which do not overexpress the ABCB1 transporter. Furthermore, the incubation of the ABCB1 overexpressing cell lines with 3 μM of verapamil, an inhibitor of the ABCB1 transporter, increased the efficacy of palbociclib similar to that of their respective parental cell lines. Similarly, the efficacy of palbociclib was decreased in HEK293 cells transfected with the ABCB1 gene, where drug resistance was mediated only by the overexpression of the ABCB1 transporter. This finding was further confirmed by the fact that the knockout of the ABCB1 gene reversed the resistance to palbociclib  produced by the overexpression of the ABCB1 transporter. However, the efficacy of palbociclib was not significantly altered in either the drug-selected or the gene-transfected cells overexpressing the ABCG2 transporter, as indicated by the similar IC50 values for palbociclib in the drug-resistant and drug-sensitive cells. Overall, these results indicated that the overexpression of ABCB1, not the ABCG2 transporter, significantly decreased the efficacy of palbociclib. Subsequently, we conducted experiments to determine the mechanism of resistance to palbociclib in cells overexpressing the ABCB1 transporter.One of the main findings of this study was that the efficacy of palbociclib was significantly lower, as indicated by the higher ICCancer cell resistance to anticancer drugs can occur due to an increase in the expression of the certain ABC transporters . TherefoIt has been reported that the hydrolysis of ATP is coupled to the drug efflux function of the ABCB1 transporter . Consequ3H]-paclitaxel accumulation assay was performed to evaluate the effect of palbociclib on ABCB1 efflux activity. Previously, it has been reported that [3H]-paclitaxel is a substrate for the ABCB1 transporter  in this study. The docking analysis indicated that the docking score of palbociclib for the ABCB1 protein was −9.616 kcal/mol, which is comparable to that of other known ABCB1 substrates, such as GSK-1070916   with the protein . Recentlcal/mol)  and WYE-cal/mol) . Also, oin vitro results indicate that the anticancer efficacy of palbociclib is significantly decreased by the overexpression of the ABCB1 transporter. In addition, it is likely that palbociclib is a substrate for the ABCB1 transporter, as palbociclib increased the ATPase activity of the ABCB1 transporter and upregulated the expression of the ABCB1 protein. Furthermore, the cytotoxic efficacy of palbociclib in drug resistant cells was restored by an ABCB1 inhibitor or the deletion of the ABCB1 gene.Overall, our