EWSR1 and members of the ETS family of transcription factors. The transcriptional activity of the fusion oncoprotein is dependent on interaction with the nucleosome remodeling and deactylase (NuRD) co-repressor complex. While inhibitors of both histone deacetylase (HDAC) and lysine-specific demethylase-1 (LSD1) subunits of the NuRD complex demonstrate single agent activity in preclinical models, combination strategies have not been investigated. We selected 7 clinically utilized chemotherapy agents, or active metabolites thereof, for experimentation: doxorubicin, cyclophosphamide, vincristine, etoposide and irinotecan as well as the HDAC inhibitor romidepsin and the reversible LSD1 inhibitor SP2509. All agents were tested at clinically achievable concentrations in 4 ES cell lines. All possible 2 drug combinations were then tested for potential synergy. Order of addition of second-line conventional combination therapy agents was tested with the addition of SP2509. In two drug experiments, synergy was observed with several combinations, including when SP2509 was paired with topoisomerase inhibitors or romidepsin. Addition of SP2509 after treatment with second-line combination therapy agents enhanced treatment effect. Our findings suggest promising combination treatment strategies that utilize epigenetic agents in ES.Ewing Sarcoma (ES) is characterized by recurrent translocations between  ETS family of transcription factors, most commonly t between the amino terminus of the EWSR1 gene and the carboxy terminus of the FLI1 gene, occurring in 85–90% of cases , but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.”If your commercial affiliation did play a role in your study, please state and explain this role within your updated Funding Statement.b) Please also provide an updated Competing Interests Statement declaring this commercial affiliation along with any other relevant declarations relating to employment, consultancy, patents, products in development, or marketed products, etc.  http://journals.plos.org/plosone/s/competing-interests) . If this adherence statement is not accurate and  there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.Within your Competing Interests Statement, please confirm that this commercial affiliation does not alter your adherence to all PLOS ONE policies on sharing data and materials by including the following statement: "This does not alter our adherence to  PLOS ONE policies on sharing data and materials.” . The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.The Reviewer #1: YesReviewer #2: Yes**********4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: The purpose of this study by Welch et al., was to define clinical agents that synergize with the LSD1 inhibitor SP2509 in Ewing sarcoma, an aggressive childhood cancer which has seen limited improvement in overall survival since the introduction of chemotherapy >50 years ago. The authors tested 7 clinically utilized chemotherapeutic agents in four different Ewing sarcoma cell lines with varying KDM1A expression levels and TP53/STAG2 mutational status. Order of addition of second line conventional combination therapy agents were also tested with the addition of SP2509.The authors should be commended on several factors including their reproducible and high throughput method for exploring antitumor effects of combinations of therapies at clinically achievable concentrations. All concentrations used in experiments were well below observed maximal plasma concentrations. In addition, it is refreshing to see that the authors used active metabolites of cyclophosphamide, irinotecan, and temozolomide which is frequently overlooked. As all experimental considerations for combination therapy were developed and conducted with the end thought of rapid translation into current LSD1 trials, data presented in this manuscript has the potential to significantly improve the survival outcomes for Ewing sarcoma patients as well as demonstrating to the scientific community how synergy experiments should be conducted. The data is technically sound with multiple replicates and each conclusion is supported by the data presented.Minor comments for considerationIntroduction1) As synergism with SP2509 was the main premise for this study, the authors should explain why SP2509 was chosen over other LSD1 inhibitors (GSK2879552 and ORY-1001). It would be helpful to state in the introduction that SP2509 is currently in Phase I clinical testing for Ewing sarcoma patients (NCT03600649) and that Ewing sarcoma cell lines are resistant to reversible inhibitors .2) To prevent confusion, it should be noted in the text that SP2509 was formally known as HCI2509.Results section1) Minor concern for this study was the decision to use Romidepsin which is only clinically approved for T-cell lymphoma. Considering the Phase 2 clinical trial of Romidepsin (NCT00112463) failed in 40 patients with metastatic or unresectable sarcoma, what is the likely hood of this HDAC inhibitor being chosen for further study in solid tumors?2) Reference is required for the following statement “HDAC1 and HDAC2 inhibitor romidepsin and the reversible LSD1 inhibitor SP2509, were selected based on their respective targets in the NuRD complex” Lines 171-172.3) Figure 1: Viability time point should be listed in the figure legend ie 24 or 72hr treatment. Image quality is also quite poor and should be corrected.4) The authors state on Line 200 that “SP2509 showed synergy with all drugs apart from vincristine”. Can the authors postulate why? Is anything known for the cell lines in terms of previous chemotherapy treatment and does this explain sensitivity/resistance to the agents tested?5) On lines 285-286, the authors elude to sensitivity of drugs may “simply be due to differences in doubling times”. This is quite possible considering the doubling times for the majority of cell lines ranges from 21-25hrs except for RDES (60hrs) . The authors should include doubling rates for each cell line in Table 1.6) Is there any correlation between sensitivity to SP2509 and the other chemotherapeutic agents tested?7) With all the different dosing schedules and agents, it was quite difficult throughout the manuscript to track which agents were synergistic over multiple cell lines. It would be nice to present a final table/figure summarizing which agents where synergistic across all four Ewing sarcoma cell lines and dosing schedules.8) Minor notes, gene names should be in italics eg Line 275 TP53 and STAG2.Discussion1) Do the authors know whether SP2509 and SP2577 have similar IC50 values? This will have implications as to whether their synergistic findings can be replicated with SP2577 in clinical settings.2) Although not used for clinical settings in Ewing sarcoma, SP2509 has been shown to synergise with docetaxel in prostate cancer . This study should be referenced.3) The dosing model presented in Supplementary Figure 2 is quite interesting and should be moved to the main text.Reviewer #2: This study describes in vitro 2D analyses of cell viability for drug combination indices of an HDAC and an LSD1 inhibitor combined with standard chemotherapies used for treatment of ewing sarcomas. Overall the experiments appear well executed and described.Although this is clearly not a mechanistic paper, the authors should better consider and discussi. the reasons supporting their hypothesis “that agents that interact with components of the NuRD complex would work synergistically with agents already utilized in the treatment of ES”.ii. the rationale behind the choice of HDAC and LSD1 inhibitors including recent comments about how SP2509 may work (PMID: 29205263 PMID:31207107)iii. possible mechanistic explanations for the results of the most and least synergistic combinations in different cell lines. For example it has been published that cells with low EWS-FLI1 expression are less proliferative PMID:28135250. Does this impact on the sensitivity of the agents used? The mechanism of action of some chemotherapeutic agents used depends on rapid cell cycling, e.g. SN-38. Can this be considered in light of A673’s relative insensitivity to topoisomerases? comments/considerations around reversal of insensitivity ofiv. the importance of scheduling. They only do one sequential experiment in which the order of drugs is changed.v. the importance around time of treatment. Activity is reported at 72hours, however drugs targeting epigenetic modifying enzymes have been shown to benefit from prolonged exposure (EZH2 inhibitors in lymphoma). Longer-term assays could be useful to achieve maximal drug efficacy and therefore give a broader overview of their activity in combination with chemotherapeutic agents.vi. Given the previous effects of LSD1 on migration (PMID:18381423) and the potential clinical significance of this phenotype, why was this not assessed or discussed?Minor comments:Page 3 line 44 sentence unclear – most commonly t between the amino … – “12” should be q12 is missing and that fuses would be better than “between”**********what does this mean?). If published, this will include your full peer review and any attached files.6. PLOS authors have the option to publish the peer review history of their article  digital diagnostic tool,  8 Aug 2019August 8, 2019Dear Editors:Please find our revised manuscript, “Small Molecule Inhibition of Lysine-Specific Demethylase 1 (LSD1) Alone and in Combination in Ewing Sarcoma Cell Lines” by Darcy Welch and Elliot Kahen et al., which we would like to submit for consideration of publication as an original research article in PLOS One. Thank you for the favorable review. We would indeed like to accept the offer of having this considered for the Targeted Anticancer Therapies and Precision Medicine Call for Papers as we agree it is within the scope of this collection. Also to clarify, there is no Sunshine Lab, LLC or commercial company involved in this research. All work done, and all authors are employees of an Academic Cancer Center. Below is a point by point response to the Reviewers’ comments.Thank you for receiving our revised manuscript and considering it for review. We appreciate your time and look forward to your response.Damon Reed, M.D., Associate Member, Department of Interdisciplinary Cancer Management and Sarcoma DepartmentsDirector of Adolescent and Young Adult ProgramMoffitt Cancer Center and Research Institute12902 Magnolia Drive, Tampa, Florida 33612. Phone: 813-745-3242, Fax: 813-745-8337damon.reed@moffitt.orgEmail: Editor Comments:1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found athttp://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf-We have ensured style requirement compliance with this version.http://journals.plos.org/plosone/s/submission-guidelines#loc-cell-lines.2. Please provide additional information about each of the cell lines used in this work, including history, culture conditions and any quality control testing procedures . For more information, please see -We have added this detail to the methods section.https://collections.plos.org/s/targeted-anticancer-therapies.3. Our staff editors have determined that your manuscript is likely within the scope of our Targeted Anticancer Therapies and Precision Medicine Call for Papers. This editorial initiative is headed by a team of Guest Editors for PLOS ONE: Andrew Cherniack, Anette Duensing, Steven Gray, Sunil Krishnan, Chandan Kumar-Sinha and Gayle Woloschak. The Collection will encompass a diverse range of research articles about the identification and classification of driver genes and somatic alterations, target and drug discovery, mechanisms of drug resistance, and early detection and screening. Additional information can be found on our announcement page: If you would like your manuscript to be considered for this collection, please let us know in your cover letter and we will ensure that your paper is treated as if you were responding to this call. If you would prefer to remove your manuscript from collection consideration, please specify this in the cover letter.-We have noted above that we would like this article to be considered for this call for papers. Thank you for this opportunity.www.nationalpcf.org). This work has been supported in part by the Translational Research Core at the H. Lee Moffitt Cancer Center & Research Institute, a NCI designated Comprehensive Cancer Center (P30-CA076292)."4. Thank you for stating the following in the Financial Disclosure section: "This study was generously supported by the National Pediatric Cancer Foundation  As synergism with SP2509 was the main premise for this study, the authors should explain why SP2509 was chosen over other LSD1 inhibitors (GSK2879552 and ORY-1001). It would be helpful to state in the introduction that SP2509 is currently in Phase I clinical testing for Ewing sarcoma patients (NCT03600649) and that Ewing sarcoma cell lines are resistant to reversible inhibitors .-Thank you for this recent reference, new since our submission (Line 65-72). 2) To prevent confusion, it should be noted in the text that SP2509 was formally known as HCI2509.-Thank you and agree. We have clarified this.Results section1) Minor concern for this study was the decision to use Romidepsin which is only clinically approved for T-cell lymphoma. Considering the Phase 2 clinical trial of Romidepsin (NCT00112463) failed in 40 patients with metastatic or unresectable sarcoma, what is the likely hood of this HDAC inhibitor being chosen for further study in solid tumors?-We agree that HDAC inhibitors have a poor track record in sarcomas when given at hematologic malignancy doses and schedules. Specific to this project, the NuRD complex may contain HDAC1 and/or 2 and we were both curious as to whether or not inhibition of HDACs would phenotypically copy LSD1 inhibition. We also anticipated the question of whether or not HDAC and LSD1 play similar roles in this complexes general function. We believe that our results show romidepsin is a promising agent for ES treatment but SP2509 is a better candidate due to less antagonism across agents. Additionally we agree with the pragmatic point of the reviewer that HDAC inhibitors are unlikely to be studied in sarcomas. Since thresholds of efficacy are much lower in vitro than in clinical trials, we wanted to explore if romidepsin had any activity worthy of further mechanistic studies. We modified the manuscript to include our reasoning in selecting romidepsin (Lines 74-77)2) Reference is required for the following statement “HDAC1 and HDAC2 inhibitor romidepsin and the reversible LSD1 inhibitor SP2509, were selected based on their respective targets in the NuRD complex” Lines 171-172.-We have added the reference as well as adding additional information on our reasoning for selection in the introduction (Line 197).3) Figure 1: Viability time point should be listed in the figure legend ie 24 or 72hr treatment. Image quality is also quite poor and should be corrected.- We are sorry about the final image quality which we’ve learned is due to the generated pdf having a process that turned 600dpi TIFF files into jpegs. We have found that in the upper right of each figure is a link that can be clicked to quickly download the figure in the high res which was indeed submitted and will be in the final publication. The figure legend has been amended with the appropriate 72hr treatment.4) The authors state on Line 200 that “SP2509 showed synergy with all drugs apart from vincristine”. Can the authors postulate why? Is anything known for the cell lines in terms of previous chemotherapy treatment and does this explain sensitivity/resistance to the agents tested?-We appreciate the suggestion to comment further on this finding. We have added a sentence in the discussion postulating why (Line 362-377). In terms of prior therapy for the cell lines, TC-71 was derived post-chemo from a biopsy of a locally recurrent tumor; TC-32 was derived post-chemo; A673 is unknown; RD-ES was derived from a primary osseous of the humerus. This info has been added to the manuscript and briefly discussed.5) On lines 285-286, the authors elude to sensitivity of drugs may “simply be due to differences in doubling times”. This is quite possible considering the doubling times for the majority of cell lines ranges from 21-25hrs except for RDES (60hrs) . The authors should include doubling rates for each cell line in Table 1.-Very helpful and we agree. We have added both the doubling time and the suggested reference.6) Is there any correlation between sensitivity to SP2509 and the other chemotherapeutic agents tested?- The strongest correlation occurs between SP2509 and DNA damaging agents. This has been added to the manuscript along with Figure 4 and a possible explanation of the mechanism (Lines 354-358).7) With all the different dosing schedules and agents, it was quite difficult throughout the manuscript to track which agents were synergistic over multiple cell lines. It would be nice to present a final table/figure summarizing which agents where synergistic across all four Ewing sarcoma cell lines and dosing schedules.-A table of the top concentrations across all 4 cell lines has been added to the supplementary tables (S3 Table).8) Minor notes, gene names should be in italics eg Line 275 TP53 and STAG2.-Thank you again, this has been fixed.Discussion1) Do the authors know whether SP2509 and SP2577 have similar IC50 values? This will have implications as to whether their synergistic findings can be replicated with SP2577 in clinical settings.- Since SP2577 involves company collaboration and review and we have limits on being able to publish data with the clinical compound, we have not included this agent in this report. We indeed tested both SP2577 and SP2509. We found that the IC50’s were similar for both compounds. SP2577 was slightly higher but on the same order of magnitude as SP2509. The company did not provide any financial support nor did they have any say in which experiments were performed. 2) Although not used for clinical settings in Ewing sarcoma, SP2509 has been shown to synergise with docetaxel in prostate cancer . This study should be referenced.-We have added this reference and comment (Lines 375-377).3) The dosing model presented in Supplementary Figure 2 is quite interesting and should be moved to the main text.-Thank you. We struggled with including this in the main text versus supplemental but are happy to include this in the main body of the manuscript. It is now Fig 5.Reviewer #2: This study describes in vitro 2D analyses of cell viability for drug combination indices of an HDAC and an LSD1 inhibitor combined with standard chemotherapies used for treatment of ewing sarcomas. Overall the experiments appear well executed and described.Although this is clearly not a mechanistic paper, the authors should better consider and discuss-We agree that this is not a mechanistic paper and more of a phenotypic paper regarding responses to agents. We do thank the reviewer for these strong comments and we hope our responses strengthen the interpretation and contextualization of the data. We agree there are many directions to go in terms of assays, schedules and time points. There are always more experiments to do and questions than answers. We are not prepared to do additional order of addition assays, or other experiments and it does not appear that this is being asked by the reviewer. We do add comments with this revision to help get these good points into the discussion to suggest next steps and to update the citations with emerging data regarding LSD1 and Ewing sarcoma.i. the reasons supporting their hypothesis “that agents that interact with components of the NuRD complex would work synergistically with agents already utilized in the treatment of ES”.-We have added to the introduction that the fusion oncoprotein is considered to be the driver of Ewing sarcoma and that the rationale for targeting both the fusion protein activity along with agents known to provide clinical benefit seems like a promising next step in treating Ewing sarcoma. It is currently unclear how the standard agents affect the fusion protein function. ii. the rationale behind the choice of HDAC and LSD1 inhibitors including recent comments about how SP2509 may work (PMID: 29205263 PMID:31207107)-We added comments and references in the introduction and discussion on our rationale in addition to reviewer #1’s comment and feel we have addressed this point up to current knowledge (Lines 65-77). iii. possible mechanistic explanations for the results of the most and least synergistic combinations in different cell lines. For example it has been published that cells with low EWS-FLI1 expression are less proliferative PMID:28135250. Does this impact on the sensitivity of the agents used? The mechanism of action of some chemotherapeutic agents used depends on rapid cell cycling, e.g. SN-38. Can this be considered in light of A673’s relative insensitivity to topoisomerases? comments/considerations around reversal of insensitivity of-We thank the reviewer for this. The comment again we feel is addressed by responses above to reviewer #1’s comment. Franzetti et al. has been added to the manuscript and we agree the results are intriguing (Lines 363-370). iv. the importance of scheduling. They only do one sequential experiment in which the order of drugs is changed.- Our initial experiment did not show significant differences in the order of addition so we decided not to investigate further. We comment that future studies exploring dose and schedule are warranted.v. the importance around time of treatment. Activity is reported at 72hours, however drugs targeting epigenetic modifying enzymes have been shown to benefit from prolonged exposure (EZH2 inhibitors in lymphoma). Longer-term assays could be useful to achieve maximal drug efficacy and therefore give a broader overview of their activity in combination with chemotherapeutic agents.-We added a comment as we do agree with this point (Line 415). vi. Given the previous effects of LSD1 on migration (PMID:18381423) and the potential clinical significance of this phenotype, why was this not assessed or discussed?-While migration assays are employed at times, we are not sure how drug effects on the migratory phenotype are applicable in the context of the performed experiments and tend to favor cell viability as the endpoint for these first screens of activity. It is difficult to imagine clinical activity from an agent that affects cell migration over viability. While we do believe migration, environment, metastases are indeed aspects of tumor biology that are tremendously important, the scope of this project was to measure viability towards translation to clinic.Minor comments:Page 3 line 44 sentence unclear – most commonly t between the amino … – “12” should be q12 is missing and that fuses would be better than “between”-We have fixed this, thank you. 26 Aug 2019[EXSCINDED]Small Molecule Inhibition of Lysine-Specific Demethylase 1 (LSD1) and Histone Deactylase (HDAC) Alone and in Combination in Ewing Sarcoma Cell LinesPONE-D-19-18074R1Dear Dr. Reed,We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.Within one week, you will receive an e-mail containing information on the amendments required prior to publication. 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Academic and non-academic emergency departments (EDs) are regularly compared in clinical operations benchmarking despite suggestion that the two groups may differ in their clinical operations characteristics. and outcomes. We sought to describe and compare clinical operations characteristics of academic versus non-academic EDs.We performed a descriptive, comparative analysis of academic and non-academic adult and general EDs with 40,000+ annual encounters, using the Academy of Academic Administrators of Emergency Medicine (AAAEM)/Association of Academic Chairs of Emergency Medicine (AACEM) and Emergency Department Benchmarking Alliance (EDBA) survey results. We defined academic EDs as primary teaching sites for emergency medicine (EM) residencies and non-academic EDs as sites with minimal resident involvement. We constructed the academic and non-academic cohorts from the AAAEM/AACEM and EDBA surveys, respectively, and analyzed metrics common to both surveys.Eighty and 454 EDs met inclusion criteria for academic and non-academic EDs, respectively. Academic EDs had more median annual patient encounters , lower median proportion of pediatric patients (6.3% vs 14.5%), higher median proportion of EMS patients (27% vs 19%), and were more commonly designated as Level I or II Trauma Centers (94% vs 24%). Median patient arrival-to-provider times did not differ (26 vs 25 min). Median length-of-stay was longer (277 vs 190 min) for academic EDs, and left-before-treatment-complete was higher (5.7% vs 2.9%). MRI utilization was higher for academic EDs (2.2% patients with at least one MRI vs 1.0 MRIs performed per 100 patients). Patients-per-hour of provider coverage was lower for academic EDs with and without consideration for advanced practice providers and residents.Demographic and operational performance measures differ between academic and non-academic EDs, suggesting that the two groups may be inappropriate operational performance comparators. Causes for the differences remain unclear but the differences appear not to be attributed solely to the academic mission. In 2017, investigators reported the clinical, educational, and research contributions of academic emergency departments (EDs) in the Unites States (US) based on the results of the Academy of Academic Administrators of Emergency Medicine (AAAEM)/Association of Academic Chairs of Emergency Medicine (AACEM) benchmarking survey . In addiThe AAAEM/AACEM survey did not allow for internal, direct comparison between pure academic and non-academic EDs, so it remained unclear if the characteristics and outcomes for the two were truly different. Other national benchmarking efforts related to ED clinical operations also exist in the US, but they too do not allow for such an internal, direct comparison. The Medical Group Management Association administers an ED survey, but it has limited clinical operations data and includes few academic programs , 5. The Since no single ED data comparison effort exists to compare appropriately the clinical operations of academic versus non-academic EDs, we sought to investigate differences between these two groups by combining data from the AAAEM/AACEM and EDBA performance surveys. Both sources are characterized by high response rates, include comprehensive clinical operations metrics, have significant overlap in their definition of clinical metrics , and theWe performed a descriptive, comparative analysis of the most current AAAEM/AACEM and EDBA ED survey results for adult-only and general EDs in the US with 40,000+ annual encounters. We excluded pediatric-only EDs and freestanding EDs because of different clinical operations outcomes and work environments (AAAEM/AACEM and EDBA report data from these EDs separately). To optimize balanced comparisons, we excluded EDs with fewer than 40,000 annual patient encounters because only one academic ED was in that volume stratum. The Johns Hopkins Medicine Institutional Review Board approved the investigation as exempt.The AAAEM/AACEM survey is administered annually to allopathic, academic emergency medicine (EM) programs with one of the following inclusion criteria: 1) full department in a Liaison Committee on Medical Education (LCME) accredited medical school, (2) division or section of another department in an LCME medical school that hosts an Accreditation Council for Graduate Medical Education (ACGME) accredited EM residency program, or (3) hospital-based department, division, or section affiliated with an LCME medical school and hosts an ACGME-accredited EM residency program . Survey  full depThe EDBA survey is administered annually to EDBA member institutions and former member institutions that submitted survey responses in prior years. EDBA membership and survey development details are available in previous publications and the EDBA website , 10, 11.Both surveys were voluntary, but respondents were afforded the incentive of receiving de-identified results and analyses of the surveys. The EDBA dataset available to the authors for analysis was de-identified , and the AAAEM/AACEM dataset was not de-identified .We excluded EDs that did not provide their annual volume or admission rate  and those missing all other clinical operations data.Our primary comparison was of operationally academic EDs (defined as a primary teaching site for an EM residency) to non-academic EDs .We constructed the academic cohort beginning with adult and general EDs from the AAAEM/AACEM survey who self-identified as a “primary academic” site. This designation ensured that the cohort included only primary teaching sites for ACGME-accredited residencies and excluded non-primary teaching sites and community sites that may have been otherwise affiliated with an academic department of EM. We verified that these EDs reported greater than 24 hours of resident coverage per day. Among the subset reporting fewer than 24 hours (presumed to be an erroneous entry) or with missing resident coverage data (n=15), we searched the program’s website or contacted the program to verify that each program met criteria as a primary teaching site. We excluded remaining EDs with fewer than 40,000 annual patient encounters.We constructed the non-academic cohort beginning with all EDs from the EDBA survey who self-reported as not being “academic”. Since academic status was not clearly defined in the EDBA survey tool, EDs responding affirmatively to “academic” status included both primary and non-primary academic EDs otherwise affiliated with an academic program. Consequently, we may have excluded sites with minimal academic mission expectations (eg. one EM resident per day), but this exclusion was necessary to maximize specificity for our non-academic cohort. Following a similar specificity strategy, we excluded any site not identifying as “academic” but still reporting more than 12 hours of resident coverage per day. We excluded remaining EDs with less than 40,000 annual patient encounters and pediatric EDs.We analyzed all operational metrics for which both surveys used a common definition. Most metrics were available directly from survey respondent entries, but some metrics (eg. admission rate) were calculated from other directly-entered values. Details of metric definitions and calculation formulae are available as supplemental material accompanying the online article.Left Before Treatment Complete (LBTC) was reported in the EDBA but not in the AAAEM/AACEM results. AAAEM/AACEM instead reported the sub-categories of LBTC including: patients leaving prior to, or following, a medical screening exam and leaving against medical advice/eloping. We added these subcategories together to calculate LBTC for AAAEM/AACEM survey respondents.We chose also to include resource utilization metrics which were queried differently in the two surveys. EDBA queried for the number of individual procedures with a modality category  performed per 100 patient encounters, and AAAEM/AACEM queried for number of patients that received one or more of each imaging modalities per encounter , raising the possibility of AAAEM/AACEM reporting lower resource utilization when compared to EDBA. We included these metrics, despite the potential for AAAEM/AACEM under-reporting compared to EDBA, because a finding of higher resource utilization among AAAEM/AACEM respondents, compared to EDBA, would be meaningful.Our analytic paradigm was that different patient populations, processes, staffing models, and implicit priorities may drive between-group variation between academic EDs, compared to non-academic EDs, more so than within-group variation. Thus, we calculated descriptive statistics and reported 95% two-sided confidence intervals, rather than hypothesis tests, because they could assess both practical and statistical significance. We avoided distributional assumptions and calculated confidence intervals for medians and interquartile ranges (IQRs) using smoothed empirical likelihood quantile estimates based on a kernel density function . For metTo maximize balanced comparisons, we performed a secondary analysis in which we used Ward’s agglomerative hierarchical clustering to create a 1:1 matched sample set on volume, ED admission rate, trauma designation, and region. Because our primary (unmatched) dataset had a greater-than 5:1 ratio of non-academic to academic EDs, we selected multiple clustering variables to maximize similarity of matched sites over a number of dimensions. Clustering only on volume risked creating a secondary dataset that was equally heterogenous, only smaller. Thus our secondary (matched) analysis included 80 unique non-academic EDs to compare with the 80 academic EDs using the same approach as the primary analysis.Among 108 US academic departments of EM sent the AAAEM/AACEM survey, 75 (69.4%) responded. All but one reported data for at least one primary academic clinical site, and five reported data for multiple primary academic sites. Among approximately 2,000 individual EDs sent the EDBA survey, 1,717 (~85.9%) responded.From the 84 primary academic adult and general EDs reported in the AAAEM/AACEM dataset, we excluded one ED with fewer than 40,000 annual visits and three EDs missing all operational data. (Pediatric EDs were reported in a separate database by the AAAEM/AACEM surveyors and therefore pre-excluded). This resulted in a total of 80 academic EDs.From the 1,651 general service US EDs in the EDBA dataset, which pre-excluded freestanding and “specialty” EDs, we excluded 343 EDs that self-identified as academic and 10 others reporting greater than 12 hours of daily resident coverage. From this non-academic subset (n=1298), we excluded 838 EDs with fewer than 40,000 annual visits. We excluded 1 ED missing all operational data and 5 remaining pediatric EDs. This resulted in a total of 454 non-academic EDs. The study flow is shown in Figure Patient volume, geographic region of the US and the American College of Surgeons trauma center level designation of the included EDs are shown in Table Tables Our comparative findings between academic and non-academic EDs related to ED admission rate, proportion of ED patients arriving via EMS, admission rate for patients arriving via EMS, and proportion of patients with high-acuity professional billing codes  codes: 99284, 99285 or 99291)  persisteThe difference in the proportion of hospital patients admitted via the ED among academic versus non-academic EDs was accounted for primarily by lower-volume academic EDs. In the 40k-59k stratum, median 60% (95% CI 50 to 67) of patients in academic centers were admitted via the ED, compared to 71% (95% CI 70 to 73) in non-academic centers. In the 60k-79k stratum, median values were 51% (95% CI 45 to 57) in academic centers and 70% (95% CI 67 to 73) in non-academic centers. In the 80k-99k and ≥100k strata, median values were similar: 66% (95% CI 59 to 71) in academic centers and 70% (95% CI 66 to 74) in non-academic centers.Magnetic Resonance Imaging (MRI) utilization appeared higher among academic centers than non-academic centers (median 2.2 [95% CI 1.7 to 2.8] encounters with MRI(s) per 100 total academic encounters, versus 1.0 [95% CI 1.0 to 1.1] MRIs per 100 non-academic encounters). This difference extinguished in the matched sample analysis, and there did not appear to be a difference between the 42 academic and 76 non-academic level I and II trauma centers who reported this metric . In general, there was no difference in the median utilization of other imaging modalities, including by volume strata or trauma designation.There was no difference in arrival-to-provider time between academic and non-academic EDs, regardless of volume stratum or trauma designation. The proportion of patients who left before treatment completion (LBTC) was higher and the median length of stay (LOS) was longer among academic EDs, differences which generally persisted across volume strata, regions, and trauma designations. The fastest quartile of academic EDs, in terms of overall LOS, were still slower than the slowest quartile of non-academic EDs. A few outlier academic EDs in the West skewed toward lower LOS. Otherwise, there were few regional LOS differences. In general, median boarding time was longer in academic EDs, most prominently in the 60k-79k and 80k-99k volume strata. While boarding times did typically increase with ED volume, there was no difference in boarding times between academic and non-academic EDs in the 40k-59k and ≥100k strata. Key flow differences are highlighted in Figure Average ED care space size varied from 193 to 1348 square feet, although the median value for academic and non-academic EDs was similar (523 [95% CI 474 to 576] versus 517 [95% CI 488 to 548]). Average care space size tended to be smaller among non-academic EDs in the West and academic EDs in the Northeast. Median annual ED visits per care space was lower for academic EDs  versus non-academic EDs .Of 76 academic EDs who reported staffing data, 39 (51%) reported using scribes, compared to 125 of 332 (38%) non-academic EDs. Scribe use increased with ED volume, with 17 of 26 (65%) academic EDs with ≥80,000 annual visits using scribes, compared to 16 of 30 (53%) non-academic EDs.The ratio of daily advanced practice provider (APP) hours to attending physician hours was similar between academic and non-academic EDs (median 0.61 [95% CI 0.51 to 0.73] versus 0.70 [95% CI 0.65 to 0.74]). However, daily patients per provider-hour (PPH)  differed among academic and non-academic EDs . While differences in boarding times were less pronounced in the matched cohort analysis, they remained significant nonetheless, suggesting that differences in hospital operations at academic centers may drive substantial differences in ED flow, despite similar ED patient acuity and volume. Better understanding of the causal factors for boarding is warranted, especially in academic centers which appear to be disproportionately affected. Other potential causes for our observed LOS differences may include: differing patient populations, differing sizes and complexity of the EDs, differing practice cultures related to extent of ED evaluations and interventions , differing inpatient operations and differing consultant practices . FinallyAcademic EDs also exhibited higher LBTC rates, a commonly cited indirect indicator of ED flow , even inPPH is another metric commonly used to measure operational efficiency. Analysis of attending coverage alone and attending plus advance practice provider (APP) coverage, revealed that mean PPH metrics were lower for academic programs in the primary analysis, but the differences extinguished in the matched analysis. When also considering resident coverage, the observed difference was not only more pronounced in the primary analysis, it also persisted in the matched analysis. The causes for the constellation of findings related to PPH are difficult to determine, but our results support that it is multi-factorial. It appeared that the teaching mission did affect PPH. On the surface, this may seem intuitive given that academic attending physicians teach while seeing patients, which will necessarily require time not committed to direct patient care, however a greater number of “extender” providers (residents) did not appear to compensate for this. We suspect that this is due at least in part to the requirement that attending physicians directly supervise resident care  while the level of supervision of APPs can be highly variable. In addition, the demands of student supervision, which were not measured in our analysis, also likely contributed to our findings. The observation that the matched analysis revealed no diffidence in PPH when considering attending and attending plus APP coverage provides evidence that the teaching mission is not the sole influence in the observed differences in PPH productivity. These other causes remain unclear, but they were likely similar to those discussed in the LOS discussion above.A few limitations in our study methodology warrant consideration when interpreting the results. The two cohorts differed in their distributions across the volume sub-cohorts. ED flow variations are known to be associated with volume . Lower vThe selection of potential survey participants also differed between the two surveys. AAAEM/AACEM was distributed to all eligible academic programs, and EDBA was distributed to EDBA members and institutions that had participated in the past. This may have created selection bias, potentially favoring EDs with heightened interest in operational processes and improvement. The survey time periods differed by six months, but there was a six month overlap and both covered a full, continuous year of data. We believe it unlikely that this affected the outcomes. While the overall response rates were favorable for both surveys, there was variability in response rates for individual survey questions with some between-survey differences, especially in the utilization data. How this may have affected the results remains unclear.Finally, our inclusion and exclusion methodology was designed to ensure greater specificity related to programs being academic versus non-academic. We believe it unlikely that we incorrectly excluded any true primary academic institutions from the AAAEM/AACEM database, however it is possible that we did exclude some true non-academic sites from the EDBA survey. This number is likely small, and it remains unclear how it may have affected the results. Nonetheless, we believe the methodology was sound in its goal of identifying true academic versus true non-academic sites.Finally, it is prudent to emphasize that the differences in clinical measures observed between academic and non-academic EDs did not allow for conclusions related to causality. One may be tempted to presume that any metric in which the academic and non-academic centers performed differently was due simply to the academic mission itself. However, our results demonstrate clearly that the two cohorts differ even in the most basic demographic characteristics, which intuitively must contribute in some part to the observed results. Furthermore, other factors unmeasured in our investigation are certain to exist. Better understanding of the root causes of the observed differences between academic and non-academic EDs is warranted as it will likely provide knowledge with which to improve clinical operations in both types of EDs.Our investigation demonstrated important differences in demographic and operational performance measures between academic and non-academic EDs. These results suggest that the two groups may be inappropriate operational performance comparators, especially when considered in the aggregate without robust and careful matching. Causes for the differences between academic and non-academic EDs remain unclear, but one should not presume them necessarily or entirely to be due to the academic mission itself. Further investigation into causal factors is warranted as this may provide information to improve operations of both types of EDs.Additional file 1:Table S1. AAAEM/AACEM ED Benchmarking Survey, Select Questions and Definitions. List of AAAEM/AACEM survey questions and associated definitionsAdditional file 2: Table S2. EDBA Benchmarking Survey, Select Questions and Definitions. List of EDBA survey questions and associated definitions


Vitis labrusca L.). The crude ethyl acetate stilbene extract obtained from the culture medium was fractionated by centrifugal partition chromatography (CPC) using a gradient elution method and the major stilbenes contained in the fractions were subsequently identified by using a 13C-NMR-based dereplication procedure and further 2D NMR analyses including HSQC, HMBC, and COSY. Beside δ-viniferin (2), leachianol F (4) and G (4′), four stilbenes (resveratrol (1), ε-viniferin (5), pallidol (3) and a newly characterized dimer (6)) were recovered as pure compounds in sufficient amounts to allow assessment of their biological activity on the cell growth of three different cell lines, including two human skin malignant melanoma cancer cell lines (HT-144 and SKMEL-28) and a healthy human dermal fibroblast HDF line. Among the dimers obtained in this study, the newly characterized resveratrol dimer (6) has never been described in nature and its biological potential was evaluated here for the first time. ε-viniferin as well as dimer (6) showed IC50 values on the three tested cell lines lower than the ones exerted by resveratrol and pallidol. However, activities of the first two compounds were significantly decreased in the presence of fetal bovine serum although that of resveratrol and pallidol was not. The differential tumor activity exerted by resveratrol on healthy and cancer lines was also discussed.In the present study, resveratrol and various oligomeric derivatives were obtained from a 14 L bioreactor culture of elicited grapevine cell suspensions ( Resveratrol and its derivatives are secondary plant metabolites widely represented in nature and described as important defense molecules acting as phytoalexins in a few plants ,2,3,4,5.Because of limitations for preparation of resveratrol and derivatives in large amounts by using conventional plant extraction procedures or chemical synthesis, the bio-production of stilbenes by plant cell suspensions in response to various elicitors such as cyclodextrins or methyl jasmonate ,20,21, wVitis labrusca L. (Concord), their separation by centrifugal partition chromatography (CPC) to study their activity on the cell viability of two human skin malignant melanoma cancer cell lines (HT-144 and SKMEL-28) and a healthy human dermal fibroblast HDF line.We report here on the production in a 14 L stirred bioreactor of various phytostilbenes from grapevine cell suspensions of −1 corresponding to a Td of 4.59 days. As currently observed with our Concord cell line, no resveratrol production occurred without elicitation (Day 0). In presence of the CDR alone, resveratrol reached about 60 mg/L during the exponential phase followed by a peak at 72 mg/L at Day 13, two days after the addition of MeJA. Then its level remained almost constant until the end of the culture with a value of 68.1 mg/L (Bioreactor culture experiments were conducted over a period of 21 days in the presence of β-cyclodextrins (CDR). Methyl jasmonate (MeJA) was only added at Day 11 of the culture. Both cyclodextrins and MeJA are known to be elicitors of stilbene production in grapevine cell suspensions ,21,22,238.1 mg/L . The pro8.1 mg/L . Only reCell suspensions were dedicated to produce enough resveratrol and derivatives to allow their purification and biological evaluation. Resveratrol bioproduction by grapevine cell cultures is now well described and use of a combined cyclodextrin-MeJA elicitation can lead to stilbene production in the g/L range ,21,22,23®), offered the possibility to collect fractions in sufficient quantities for further chemical analyses and biological assays. The CPC fractions eluted with the organic mobile phases over the gradient in the ascending mode contained all bio-produced stilbene derivatives and represented 73% of the injected mass, while the most hydrophilic compounds of the extract mainly including residual cyclodextrins and culture medium nutrients were well-retained inside the CPC column.In a single run of 160 min, 1.5 g of the crude ethyl acetate stilbene extract obtained from the culture medium was fractionated by centrifugal partition chromatography (CPC) using a gradient elution method. CPC is a solid support-free separation technique involving the distribution and the transfer of solutes between at least two immiscible liquid phases according to their distribution coefficient. The CPC column used in this work, with a total capacity of 303 mL and only 231 partition cells  and 221 rows . This table was submitted to Hierarchical Clustering Analysis (HCA) on the rows. As a result, statistical correlations between 13C-NMR resonances belonging to a single structure within the fraction series were visualized as “chemical shift clusters” in front of the corresponding dendrograms.The major stilbenes contained in the CPC fractions were firstly identified by using a rocedure ,25. All 13C-NMR chemical shifts. After entering these chemical shifts into a database containing 13C-NMR data of natural compounds, including 101 known stilbene structures from different plant genera, the structure of trans-resveratrol (1) was proposed as the first hit out of 60 proposals. This structure was confirmed by checking all the chemical shifts of trans-resveratrol in NMR spectra of fractions F1 in which the intensity of cluster 1 was predominant. By using the same method, clusters 2, 3, and 5 were identified as δ-viniferin or maximol A (2), pallidol (3), and ε-viniferin (5). Clusters 4 and 4′ corresponded to leachianol F (4) and leachianol G (4′), respectively, which were both present as a diastereoisomer mixture in fractions F10 and F11. Cluster 6 did not match with any known stilbene molecular structure stored in our database. Further 2D NMR analyses including HSQC, HMBC, and COSY were performed on fractions F5 and F6 containing the signals of cluster 6, leading to the identification of a new resveratrol dimer (6) which has never been described previously. To our knowledge, only one report has described the chemical synthesis of a methoxy-substituted derivative of this compound together with a series of other hydroxystilbene analogs in order to investigate the catalytic action of a laccase from Trametes pubescens on the dimerization of hydroxystilbenes  assay (Sigma-Aldrich) . After Mt-test.The data were expressed as the mean ± SD of 3 independent experiments. Each experiment was performed in triplicate. The significance of differences was established with the Student’s Vitis labrusca L.). Four stilbenes ) were recovered in sufficient amounts to allow assessment of their biological activity on the cell growth of two human skin malignant melanoma cancer cell lines (HT-144 and SKMEL-28) and a healthy human dermal fibroblast HDF line.In the present study, resveratrol and various oligomeric derivatives were obtained from elicited grapevine cell suspensions (6) have shown a high inhibiting activity of the cancer cell viability (higher than the one displayed by resveratrol), although this activity was significantly decreased in the presence of FBS. Some studies have previously evidenced a synergistic action of stilbenes used in combination compared to resveratrol alone [V. vinifera cell suspensions on the viability of various cancer lines has been observed over resveratrol alone [6) and resveratrol used in combination could thus be envisaged in further works.It is clear from all the results obtained that resveratrol shows the best anti-cancer properties as its efficiency on cancer cell viability does not seem to be affected by the presence of fetal bovine serum. Moreover, this compound displayed a tumor-specificity. Oligomers like ε-vniferin and the dimer (ol alone ,45. Nameol alone . A syner


Nanoscale zero valent iron has been a widespread concern in various fields due to its large specific surface area and high reactivity. However, nanoscale zero valent iron (nZVI) is very likely to aggregate and be oxidized, which limit its wide application in industry. Most clay minerals have a large adsorption capacity of cations due to their negative charges and high specific surface areas. In the present work, nZVI was loaded onto two typical clay minerals: kaolinite and sepiolite, to inhibit its oxidation and aggregation. The composites were applied to degrade Rhodamine 6G (Rh 6G) under microwave irradiation. The effects of pH value and microwave power on degradation were studied. The results showed that the removal amount of Rh 6G by nZVI/kaolinite was 110 mg/g in 15 min, while it reached 300 mg/g by nZVI/sepiolite. The difference between these two composites was mostly determined by the structures of these two clay minerals. About 80% of the textile wastewater comes from the textile printing and dyeing industry every year, which is an industrial sector with large water consumption and high discharge of wastewater  to degrade organic dyes  and sodium borohydride (NaBH4) were purchased from Beijing Chemical Workstation. Rh 6G was from Aladdin. All the chemicals were of analytical grade. The sepiolite was obtained from Sigma Aldrich, its BET area and average pore size are 319.4 m2/g and 6.885 nm, respectively. The kaolinite was bought from China Kaolin Co, Ltd, its BET area and average pore size are 22 m2/g and 30.095 nm, respectively. All the chemicals and minerals were used without further purification. All of the solutions were formulated with distilled water.Iron (III) chloride hexahydrate  and 10 g FeCl4 before the next trial. All experiments were run in duplicates.2,000 mg Rh 6G was dissolved in 500 mL distilled water and ultrasonic for 15 min to prepare 4,000 mg/L Rh 6G solution. In batch experiments, 0.1 g as prepared sample was added in 10 mL Rh 6G solution, then, the mixture was placed in a microwave oven to degrade Rh 6G for a certain time under different microwave power. After the degradation, the mixture was centrifuged and the supernatant was filtered through 0.22 μm syringe filters before being taken to a UV-Vis spectrophotometer for the analysis of equilibrium concentrations. In the cycle test, the used nZVI/clay was reduced by NaBH−1 with a scanning step length of 0.01°. Scanning electron microscopy (SEM) was used to record the surface morphology of the samples, carried out on a scanning electron microscope (JSM-IT300) with conditions at 30 kV and 10−4 Pa. The equilibrium concentration of Rh 6G was determined by a UV-Vis spectrophotometer (UV2400/PC), the value of the absorption coefficient at 525 nm. The surface compositions of samples were tested by an X-ray photoelectron spectrometer (K-Alpha), which can analyze the valence of elements in samples, especially valence state of iron element. The microwave network analyzer N5244A (Agilent) was used to analyze microwave absorption properties of flexible absorbing film. The frequency range was from 2 to 10 GHz. Automated gas sorption analyzer (Autosorb-iQ-2MP) was used to analyze the specific surface area of the samples. Zeta potential was recorded by nanoparticle size potential analyzer (Zetasizer Nano ZS90). The coaxial wire method was adopted for the analysis.The crystal diffraction data was determined by the X-ray diffractometer (Rigaku D/Max-IIIa X-ray diffractionmeter) with a CuKα-radiation at 30 kV and 20 mA operating conditions. Angle ranged from 3 to 70° and the speed was 8° min0 (JCPDS No. 06-0696). No obvious characteristic peaks of iron oxides was founded in the nZVI/kaolinite or nZVI/sepiolite, indicating that nZVI was not oxidized or only a very small part was oxidized during the synthesis process. Besides, the patterns of the composites stayed almost the same before and after the loading, suggesting that the structures of clay minerals not yet destroyed, and nZVI is loaded on the surface of mineral material rather than intercalated in this study.The composites were synthesized by liquid phase reducing method. The structures of nZVI, kaolinite, speioilte and the composites were showed in Figure The SEM results in Figures While loading onto sepiolite, most of the nZVI particles were attached to the fibers within a size range of 20–45 nm.Figure The color of materials changed to black after the addition of nZVI and nZVI/clay. As time went by, the color of both materials become lighter gradually due to the oxidation of nZVI. However, nZVI/clay showed a better resistance to oxidation than nZVI as the color of nZVI suspension changed from black to yellow completely after 72 h while the color of nZVI/clay suspension just started to turn yellow after the same time. It indicated that only a small portion of nZVI was oxidized after loading, which means that loading nZVI onto clay could effectively inhibit its oxidation.0 in nZVI/sepiolite and nZVI/kaolinite. The other two peaks at binding energies of 713.5 and 726.5 eV could be attributed to the 2p3/2 and 2p1/2 peaks of Fe (III) in nZVI/sepiolite while 716 and 726 eV in nZVI/kaolinite, indicating that a small part of Fe0 on the surface of the composite was oxidized to Fe (III).The surface compositions of nZVI/kaolinite and nZVI/sepiolite and the valence state of Fe on its surface were analyzed by XPS technique. The survey spectrum of this sample was shown in Figure The ability of a substance to absorb microwaves is mainly determined by its dielectric loss factor. A substance with a large dielectric loss factor usually has a strong ability to absorb microwaves. On the contrary, a material with a small dielectric loss factor has a weak ability to absorb microwaves. The dielectric loss (tan δe = ε″/ε′) of nZVI/kaolinite and nZVI/sepiolite was analyzed by a microwave network analyzer Figure . The dieTable 0 was gradually oxidized to Fe3+ and generated hydroxyl radicals (HO•) and superoxide radicals  were added to solutions during the reaction (Figure • and In order to prove the main active ingredient that degrades Rh 6G are HOn Figure . It is w• and In summary, the aggregation and oxidation of nZVI can be effectively inhibited by loading nZVI on clay minerals. When the composites were used to degrade Rh 6G under microwave irradiation, nZVI/sepiolite exhibited better removal performance than nZVI/kaolinite, due to the difference in iron loading amount, which was caused by the difference in specific surface area and zeta potential. In addition, composites could be reused for several times after regeneration. With the addition of different types of scavengers, it was demonstrated that HOWR and GL conceived the project. GL and LL designed and performed the experiments. DW analyzed the data. WR and GL wrote the manuscript.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.


Although cyclin-dependent kinase (CDK) 4/6 inhibitors have exhibited remarkable results for patients with estrogen receptor (ER)–positive breast cancer in clinical trials, the mechanism of CDK4/6 inhibitor resistance remains unclear. Thus, this study aimed to investigate the mechanism of CDK4/6 inhibitor resistance using two CDK4/6 inhibitor resistant breast cancer cell lines. We established CDK6 overexpressed cell lines (MCF7-C6) from MCF-7 cells using the stably transfected CDK6 expression vector. Additionally, acquired ribociclib-resistant (RIBR) cell lines were created using ER-positive hormone-resistant cell lines by long-term exposure to ribociclib. CDK6 overexpression and the knockdown of CDK4 experiments highlight the significance of high levels of CDK4 and low levels of CDK6 in CDK4/6 inhibitor sensitivity. Moreover, RIBR cell lines did not exhibit incremental CDK6 compared with ER-positive hormone-resistant cell lines. In MCF7-C6 and RIBR cell lines, p21 levels decreased, and p21 levels were proportional to CDK4/6 inhibitor sensitivity. This study suggests that overexpression of CDK6 is one of the many possible mechanisms of resistance to CDK4/6 inhibitors. Furthermore, p21 levels have the potential to serve as a marker for CDK4/6 inhibitors independent of the resistance mechanism. Until recently, the primary therapeutic options for postmenopausal women with estrogen receptor (ER)–positive human epidermal growth factor receptor 2 (HER2)-negative metastatic breast cancer (MBC) were predominantly comprised of hormonal therapy , 2. AlthIn recent years, cyclin-dependent kinase (CDK)4/6 inhibitors have been developed as a revolutionary class of novel drugs, exhibiting excellent outcomes in clinical trials, which resulted in their approval and clinical use worldwide –12. PrimCDK families are essential in the cell-cycle regulation, making them a therapeutic target to interfere with the cell-cycle division and proliferation. A complex of CDK4 and CDK6 with cyclin D results in the activation of CDK4/6, which initiates the phosphorylation and inactivation of retinoblastoma (Rb) protein, resulting in immigration to the S-phase of the cell cycle –16. CDK4In this study, we established acquired CDK4/6 inhibitor–resistant cell lines from hormone-resistant cell lines with positive ER expression. Almost all patients with ER-positive breast cancer were administered antihormonal drugs as adjuvant therapy. In addition, a CDK4/6 inhibitor was prescribed in combination with antihormonal drugs in cases of MBC. Hence, the addition of AI resistance to CDK4/6 inhibitor resistance is a plausible method for elucidating the resistance mechanism and assessing effective therapeutic options following resistance to CDK4/6 inhibitor, although CDK4/6 inhibitors are used as first-line therapy of MBC.This study aimed to assess the impact of CDK4 and CDK6 expression levels on the CDK4/6 inhibitor sensitivity. In addition, we intended to establish ribociclib-resistant cell lines from estrogen deprivation–resistant (EDR) 1 as ER-positive hormone-resistant cell lines, elucidate the mechanism of CDK4/6 inhibitor resistance, and investigate the effective therapeutic options following CDK4/6 inhibitors resistance.First, we assessed the efficacy of ribociclib for each subtype of breast cancer cell lines. Compared with non-luminal-type cell lines , luminal-type cell lines (MCF-7 and T-47D cells) suppressed cell growth to a large extent . The mosIn this study, we established three clones of CDK6 overexpressed cell lines (MCF7-C6 V1-3) from MCF-7 by stably incorporating the transfected CDK6 expression vector in order to explore the molecular mechanism of the ribociclib sensitivity . ConcurrWe performed CDK4 knockdown experiments using CDK4 siRNA in MCF7-C6 Ctrl and MCF7-C6 V1 cell lines to further investigate the molecular mechanism of ribociclib sensitivity. With the CDK4 knockdown, we created cells with four different expression patterns of CDK4 and CDK6 . RibocicAfter long-term culture under conditions of sufficient doses of ribociclib, we established acquired resistant cell lines for ribociclib  from EDR1 . RIBR ceWe assessed the efficacy of other CDK4/6 inhibitors on MCF7-C6 and RIBR cell lines, which have different resistant mechanisms. MCF7-C6 cell lines displayed lower sensitivity to palbociclib than MCF7-C6 Ctrl cell lines . In addiIn MCF7-C6 and RIBR cell lines, we assessed the protein levels of cell-cycle regulatory agents by immunoblot analysis. We focused on the CDK4 expression levels and its related factors at first because the CDK4:CDK6 ratio might be associated with the CDK4/6 inhibitor upon investigation. We observed no remarkable changes in the total Rb, CDK4, and cyclin D1 between MCF7-C6 and MCF7-C6 Ctrl cell lines . In contWe investigated the efficacy of molecular-targeted and chemotherapeutic drugs in MCF7-C6 and RIBR cell lines using the following: alpelisib; α-subunit-specific PI3K inhibitor, everolimus; mTOR inhibitor and U0126; MEK inhibitor. In addition, MCF7-C6 cell lines exhibited suppressed cell growth by these three molecular-targeted drugs equivalent to MCF7-C6 Ctrl cell lines –5C. WhilFinally, we assessed the efficacy of long-term ribociclib depletion to RIBR cell lines. We established RIBR(-R) cell lines from RIBR cell lines by long-term culturing without ribociclib . We obtaAt present, CDK4/6 inhibitors are promising given the outcomes observed in clinical trials –12. DespThe study illustrated that ribociclib sensitivity varied between luminal and non-luminal cell lines. In addition, ribociclib was found to be effective in all hormone-resistant cell lines similar to MCF7-E10 cell lines independent of the mechanism of hormonal therapy resistance  and 1C. Acquired CDK6 amplification has resulted in breast cancer resistance to CDK4/6 inhibitors ; howeverIn contrast, the RIBR model of acquired resistance to CDK4/6 inhibitors exhibited CDK6 expression levels similar to EDR1. Although CDK4 expression levels in RIBR cell lines were marginally decreased compared to EDR1 , a mild As the major functional mechanism of CDK4/6 inhibitors is thought to promote late G1 stage by inhibiting S-phase immigration i.e., not cytotoxic but cytostatic activity, CDK4/6 inhibitor-resistant cells could reasonably restore the sensitivity to CDK4/6 inhibitors without the presence of these drugs after a considerable lag. Overall, p21 expression levels could play a vital role in the sensitivity to CDK4/6 inhibitors because ribociclib sensitivity was proportional to p21 expression levels. CDK4/6–cyclin D complex plays a crucial part in breast cancer, with high sensitivity to CDK4/6 inhibitors, such as luminal-type and hormone-resistant cell lines  and 7B. To date, effective therapies following CDK4/6 inhibitor resistance remain partially elucidated. Regarding targeted therapies, only everolimus is available for clinical use, and it has not shown promising results . In the in vitro. Experiments on animal models are required to confirm our results. Furthermore, we should confirm the relationship between effect of these drugs and potential biomarkers through tissue and blood samples.In the present study, we demonstrate the multiple mechanisms of CDK4/6 inhibitor resistance and potential biomarkers of CDK4/6 inhibitors Our findings suggest that the mechanism of CDK4/6 inhibitor resistance exists in multiple forms and that the levels of CDK4 and CDK6 are potential biomarkers of CDK4/6 inhibitors, which may be especially useful for the selection of patients to estimate the sensitivity in breast cancer. Further, p21 could serve as a monitoring marker for CDK4/6 inhibitors. Nevertheless, further studies are warranted to elucidate the mechanism of CDK4/6 inhibitor resistance, as the findings are anticipated to provide crucial insights into considering an indication for a biomarker and monitoring marker for the resistance to CDK4/6 inhibitors.We purchased ribociclib, palbociclib, and abemaciclib from Selleck Chemicals  and obtained alpelisib from Santa Cruz Biotechnology Inc. . In addition, fulvestrant was acquired from Sigma–Aldrich , paclitaxel and U0126 were purchased from Cell Signaling Technology . Everolimus was obtained from LC laboratories, Inc. , and eribulin was acquired from Eisai .In western blotting, the sources of antibodies were as follows: total Rb (#9309), pRb , cyclin D1 (#2922), cyclin E1 (#20808), CDK2 (#2546), CDK4 (#12790), CDK6 (#13331), p21 (#2947), p27 (#2552) and β-tubulin (#2146)—all acquired from Cell Signaling Technology. In addition, we purchased horseradish peroxidase–conjugated secondary antibody from Bio-Rad Laboratories Inc. .2.Promega provided authentication for MCF-7, T-47D, MDA-MB-231, BT20, and SKBR3 cell lines using STR-PCR. All experiments were completed within 15 passages. We stably transfected MCF7-E10 breast cancer cells derived from MCF-7 with ERE-GFR reporter plasmids as reported previously [In inhibitor sensitivity assays, we maintained parent, MFR, and MCF7-C6 cell lines in RPMI-1640 medium containing 5% FCS, seeded in 24-well culture plates and grown to approximately 50% confluence, added each drug for three consecutive days, harvested, and counted cells using a Sysmex CDA-1000 Automated Cell Counter . EDR, RIBR, and RIBR(-R) cell lines were cultured in phenol red–free RPMI-1640 medium.® HD Cloning Kit (TAKARA Bio Inc), CDK6 fragment was ligated into the pBApo-CMV Pur DNA expression vector, which had been digested with BamHI and HindIII. We transfected the obtained CDK6 expression vector into MCF-7 using the Trans IT LT-1 Transfection Reagent . In addition, stable cell lines were established after selecting puromycin (1 mg/mL). Furthermore, all DNA products were confirmed by sequencing. The sequences of primers were as follows: forward, 5′-TTA GTG AAC CGG ATC CAT GGA GAA GGA CGG CCT GTG -3′ and reverse, 5′-AGC CTC CCC CAA GCT TTC AGG CTG TAT TCA GCT CCG AG-3′.Using PCR, we amplified the fragment of the CDK6 coding region. The pBApo-CMV Pur DNA  plasmid was digested separately using BamHI and HindIII restriction endonuclease. Using In-FusionWe seeded MCF7-C6 cell lines into a 6-cm culture dish for the immunoblot analysis or 24-well culture plates for the cell proliferation assay in RPMI-1640 medium. After growing cells to approximately 50% confluence, the CDK4 or nonspecific control small interfering RNA  was transfected using the Lipofectamine RNAiMAX Transfection Reagent  per the manufacturer’s instructions.The cells were plated into a 6-cm culture dish and grown to approximately 80% confluence before adding each drug. After 24 h, cells were retrieved by trypsin treatment and fixed with 70% ethanol. The nuclei were stained with propidium iodine and analyzed on the LSR Fortessa .We plated 3000 cells into 6-well culture plates and replaced fresh medium and drugs every 2 or 3 days and cultured for 15 days. In addition, colonies were fixed with 4% paraformaldehyde phosphate buffer solution  and stained with 0.3% crystal violet .We prepared cell lysates using the Lysis-M Reagent  supplemented with the PhosSTOP phosphatase inhibitor cocktail (Roche Diagnostics) per the manufacturer’s instructions. Then, extracted proteins (5 μg) were separated on 12% SDS–PAGE using acrylamide gels, and proteins were transferred to PVDF membrane. In addition, we determined protein expression by western blotting with specific antibodies listed in the reagents section and detected expression signals on the ImageQuant™ LAS 4000 Image Analyzer  using Immun-star HRP substrate (Bio-Rad).We performed three individual experiments of the cell proliferation assay and immunoblot analysis. Cell proliferation assays of CDK4 siRNA were performed in duplicate.t-test to assess significance differences between two groups performed in triplicate. All data are expressed as means ± standard deviation (SD). All statistical analyses were performed using VALIDHTML. We considered P-values of < 0.05 as statistically significant in this study.We used the Student’s


Pallister-Killian syndrome (PKS) (OMIM:#601803) is a rare sporadic genetic disorder characterized by multi-malformations which is caused by the presence of the extra isochromosome 12p. PKS is featured by the tissue-limited mosaicism of the isochromosome 12p [i(12p)]. There were a wide spectrum of prenatal ultrasound findings of PKS, which made it difficult to be found in first or second trimester. Polyhydramnios, diaphragmatic hernia, and rhizomelic limb shortening were the most common prenatal ultrasound abnormalities in PKS. This study retrospectively analyzed the ultrasound findings and molecular cytogenetic results of four PKS fetuses diagnosed by using cord blood samples.The ultrasound anomalies of four PKS fetuses are described as follows: fetal macrosomia, cerebral ventriculomegaly, increased NT thickness, rhizomelic limbs shortening, polyhydramnios. Biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), femur length (FL) measurements were above the mean in three fetuses,while one fetus showed rhizomelic limbs shortening. Combined with this study and previous literature, polyhydramnios was the most frequent anomaly observed in prenatal ultrasound examination of PKS, which accounted for 48% (94/194). Fetal macrosomia was present in 15% (29/194), cerebral ventriculomegaly in 13% (25/194), thickened nuchal fold in 9% (18/194), rhizomelic limbs shortening in 26% (51/194). I(12p) was found in the karyotype analysis of cultured cord blood lymphocytes and the mosaic ratios ranged from 2 to 5%. Single nucleotide polymorphisms array (SNP-array) results suggested that the whole short arm of chromosome 12 was duplicated with 2~3 copies. Fluorescence in situ hybridization (FISH) was performed to confirm the results of karyotype and SNP-array.In case non-specific indicators such as fetal macrosomia, polyhydramnios and rhizomelic limbs shortening are observed meanwhile in prenatal ultrasound, targeted detection of PKS should be considered. In the prenatal diagnosis of PKS, the combination of SNP-array and FISH with conventional karyotype are the key to seek i(12p) and for precise diagnosis. Pallister-Killian syndrome (PKS) OMIM:#601803) is a rare sporadic genetic disorder characterized by developmental delays, prominent foreheads, sparse frontotemporal hairs, craniofacial deformities, mental retardation, epilepsy, low tension, skin pigmentation, congenital heart defects and other systemic abnormalities. The feature of this syndrome is the presence of isochromosome 12p [i(12p)] mosaicism with tissue-limited. Tissue-limited mosaicism refers to the differences in chromosome between different tissues in the same individual. The percentage of cells with i(12p) depends on the tissue examined, regardless of the severity of the syndrome [803 is a Prenatal diagnosis of PKS remains a challenge because of the difficulty in detecting additional i(12p) and the diversity of mosaicism level. Moreover, the supernumerary marker chromosomes are easily decreased in amniotic fluid cell culture . Using tSingle nucleotide polymorphisms array (SNP-array) can detect copy number variations using DNA isolated from uncultured specimens . In thisWe retrospectively analyzed the ultrasound and genetic results of all fetuses diagnosed with PKS in our medical genetic center between January 2017 and December 2018. The follow-up were performed by experienced nurse. We reviewed the ultrasound findings of PKS published in the last decade in order to identify the anomalies and markers existing in PKS. This study obtained the informed consent of all involved women and was approved by the Ethics Committee of Guangdong Women and Children hospital.Voluson E8  was applied for ultrasound examinations, which were performed by specialists experienced in fetal medicine. The gestational weeks of all the involved women exceeded 26 weeks when they were referred to our center. Subsequent cordocentesis were performed and 2 mL cord blood were aspirated into asepsis pipe and sent to the laboratory as soon as possible. All specimens were divided into two parts, one for cell culture and one for molecular genetic testing after DNA isolation using QIAamp DNA Blood Mini Kit . NANODROP 2000  was applied to determine DNA concentration. CytoScan 750 K chip  was used for SNP-array. All the procedures were operated according to the manufacturer’s protocol. The results were analyzed with ChAS3.1.0.15  software. The remaining samples were employed for routine cell culturing according to standard culture process. Karyotypes were obtained after GTG-banding. Fluorescence in situ hybridization (FISH) was performed to confirm the diagnosis of PKS using chromosome 12p telomere probe  and control chromosome 16 centromere probe .The mean age of the women was 32 years and the mean gestational age was 30 weeks. All the pregnancies were singleton and the women had unremarkable history. Two women were primigravida and the other had healthy children. Anomalies of ultrasound findings were as followed: fetal macrosomia, cerebral ventriculomegaly, increased NT thickness, rhizomelic limbs shortening, polyhydramnios. The descriptions of ultrasound findings were summarized and demonstrated in Table Since the gestational weeks were all over 24 weeks, all 4 cases received invasive prenatal diagnosis with cordocentesis. Karyotype, SNP-array and FISH results of 4 fetuses were shown in Fig. PKS is difficult to detect in prenatal diagnosis because most cases were sporadic. Less than 100 prenatal cases have been published since first described by Gilgenkrantz in a prenatal diagnosis of tetrasomy 12p from amniocytes . SantamaFetuses with PKS exhibited a very typical growth pattern characterized by increased BPD and HC, usually above the 90th percentile, accompanied with femoral growth delay, which is significantly below the 10th percentile for gestational age. In our study, the HC percentile of four fetuses was 100th, 90th, 99th, and 32th respectively. But the percentile of FL was higher than 10th, except that of fetus 4 (2th). This further illustrated the varity of ultrasound manifestations of PKS. Karaman et al. presented 15 children with PKS, two of whom were macrosomia . SalzanoPKS is caused by the presence of additional i(12p). It is difficult to detect i(12p) cells in cord blood due to the low response of lymphocyte in phytohemagglutinin (PHA) stimulation , 17. I(1The mechanism of i(12p) formation is still not fully revealed. Previous literatures have illustrated that maternal meiotic II nondisjunction is a mechanism of tetrasomy 12 mosaicism, although there were several reports of paternal nondisjunction , 23. SimIn conclusion, our study presented the atypical expression of PKS in prenatal diagnosis such as ultrasound finding and diagnostic samples. In case non-specific indicators such as fetal macrosomia, polyhydramnios and rhizomelic limbs shortening are observed meanwhile in ultrasound examination, targeted detection of Pallister-Killian syndrome should be considered, including expanded cell counts in karyotype and using uncultured genomic DNA for molecular detection.