The active state of centromeres is epigenetically defined by the presence of CENP-A interspersed with histone H3 nucleosomes. While the importance of dimethylation of H3K4 for centromeric transcription has been highlighted in various studies, the identity of the enzyme(s) depositing these marks on the centromere is still unknown. The MLL (KMT2) family plays a crucial role in RNA polymerase II (Pol II)-mediated gene regulation by methylating H3K4. Here, we report that MLL methyltransferases regulate transcription of human centromeres. CRISPR-mediated down-regulation of MLL causes loss of H3K4me2, resulting in an altered epigenetic chromatin state of the centromeres. Intriguingly, our results reveal that loss of MLL, but not SETD1A, increases co-transcriptional R-loop formation, and Pol II accumulation at the centromeres. Finally, we report that the presence of MLL and SETD1A is crucial for kinetochore maintenance. Altogether, our data reveal a novel molecular framework where both the H3K4 methylation mark and the methyltransferases regulate stability and identity of the centromere. This study reveals that MLL and SETD1A regulate transcription and H3K4 methylation on centromeres to ensure kinetochore maintenance and CENPA deposition; how both the H3K4 methylation mark and the enzyme are required to ensure centromere stability. Centromeres are specialized regions on chromosomes that form a scaffold of the kinetochore, a multi-protein complex that links chromosome to spindle microtubules to facilitate faithful chromosome segregation during mitosis; failure of this process leads to chromosomal structural and numerical abnormalities often seen in pathological conditions such as cancer . CentromSu(var)3-9, Enhancer-of-zeste, Trithorax (SET) domain that is responsible for the methyltransferase activity of these enzymes. In addition, some members like MLL and MLL2 also use the transcription activation domain (TAD) to promote transcription [In eukaryotes, the lysine methyltransferase 2  family of proteins deposit the H3K4 methylation marks. In humans, there are 6 members in this family including MLL1 (MLL or mixed lineage leukemia protein), MLL2, MLL3, MLL4, SET Domain Containing 1A (SETD1A), and SETD1B. While SETD1A is a global H3K4 tri-methyltransferase, MLL1-4 displays locus-specific methylation activity –28. All cription . Differecription . In factcription ,32. HoweMLL family members are involved in a wide variety of roles. However, the role of these proteins in mitosis is recently coming to light. Interestingly, all mitotic functions described so far for the members of this family are involved in averting chromosome mis-segregation and thus maintaining genomic integrity –37. We hSeveral studies have shown that centromeres are transcribed by RNA Pol II in a unique environment on chromatin decorated with histone modification like H3K4me2 and H3K36me2 ,38. HoweAPOL4, PAX3, and HBB. Once we knocked down different MLL family members, we observed a reduction in all 3 array-specific transcripts from chromosome 17  or made recombinant siRNA-resistant constructs by introducing silent mutations  for MLL and RAD18 for SETD1A as positive control [HOXA9 and RAD18 promoters, respectively, we observed that their enrichment was also significantly reduced on the α-satellite loci  using a specific antibody against MLL or SETD1A and checked for their binding on the centromeres in HEK-293 cells . We used control ,49. In oite loci . Second,ite loci . We simuite loci , indicatite loci  and IMR9ite loci . AltogetHOXA9 promoter. After successfully replicating these ChIP experiments in the iKO cell lines several times, we interrogated the effect of loss of MLL on H3K4 dimethylation levels. As expected, the H3K4me2 levels were dramatically reduced in both MLL iKO cell lines  assay in MLL or SETD1A siRNA-treated cells. The RNase H treated genomic DNA before the DRIP assay worked as a control to ensure a specific signal . An R-lo exon 8; ), acted and EGR1 ,59, and C region  acted asC region ,56. We cS2P)  , via IF 2P)  was performed 72 h after siRNA treatment and differential gene expression (DGE) signatures of Control Vs MLL KD, and Control Vs SETD1A KD were examined . MLL depEven though transcript levels of all proteins being analyzed here in Figs –7 remaincis by modulating transcription of cenRNAs at centromeres or CCTT at Chromosome 17, and therefore impacting the recruitment of centromere proteins (like CENP-C) or in trans by regulating transcription of centromeric/kinetochore gene (like CENP-B and CENP-H). All in all, loss of MLL and SETD1A have an adverse effect on the maintenance of kinetochores.While this paper was in revision, Zhang and colleagues reported that a long noncoding RNA (lncRNA) named CENP-C targeting transcript (CCTT), interacts with CENP-C through specific RNA–protein interactions and regulates CENP-C level at centromeres . As MLLsBoth CENP-C and CENP-B participate at different levels to stabilize CENP-A nucleosomes –76. FurtIn order to confirm that the loss of CENP-A observed here is not due to reduced cell proliferation upon loss of MLL or SETD1A ,77,78, wThe discovery of the active histone mark—H3K4me2—within the centrochromatin and the elegant demonstration of its crucial role in kinetochore maintenance using targeted-engineering of HAC, has firmly established the importance of this mark in kinetochore function. However, experimental evidence identifying which of the many histone lysine methylation enzymes deposits this mark on the centromere, was lacking. Despite differences in size, structure, interacting partners, and catalytic potential, the various members have been grouped under the MLL (KMT2) family banner by virtue of their SET domain. Even though each of these proteins is uniquely required during development, redundant roles of these enzymes are well known ,80. In tOur results suggest that MLL affects the kinetochore assembly and maintenance in multiple ways. Not only is the presence of the SET domain in MLL required at the centromere to deposit the H3K4me2 mark, but it also co-activates centromeric transcription by its TA domain. Both these activities are pertinent in recruiting key proteins like CENP-C and HJURP to the centromere and therefore loading of CENP-A at the centromere. In fact, our results indicate that loss of rapid transcription (by deletion of TAD) exhibits a pronounced effect on de novo CENP-A incorporation in our assay, even though the decrease in cenRNA transcripts by loss of both TAD and SET-domain deletion is comparable Figs . It is iOverall, loss of CENP-A is tolerated by the cell with chromosome segregation defects appearing after multiple rounds of cell division ,6,15. WeS2P (and R-loops) in MLL iKOs . An increase in aberrant R-loops can lead to DNA double-strand breaks at several genomic locales and challenge centromere integrity [Our quest on understanding mitotic roles of MLL highlights the fact that loss of these proteins have a pleiotropic effect on cellular processes making it hard to attribute one defect to one process. Even though we performed RNA-seq experiments to gauge the impact of MLL’s transcriptional function on its role in the deposition of CENP-A, we cannot discount the fact that our HMT(s) do regulate the expression of a large number of genes ,45–48. Fntegrity ,54,86. Integrity –89, a phntegrity . Hence, S2P at the centromere depicting an aberrantly “paused” RNA Pol II in MLL iKO cells. Indeed, a stalled RNA pol II is associated with R-loop formation [S2P and serine 5-phosphorylated RNA Pol II (RNA Pol IIS5P) forms have been reported at others [Previous studies report a positive correlation between transcription, H3K4me2 mark and R-loop formation ,90, and ormation . Loss oformation ,46,63. Wt others ,46. A reS2P in the absence of SETD1A on the centromere. Our data indicate that the total RNA Pol II as well as RNA Pol IIS2P levels decreased upon loss of SETD1A. These observations are in contrast to studies conducted in yeast Saccharomyces cerevisiae, which show that deletion of the only H3K4 methyltransferase (Set1A) in the cell has little effect on the recruitment of RNA Pol II on constitutive euchromatin [S2P fell progressively in the absence of H3K4me2 in HAC [S2P levels decreased here as a cause or consequence of SETD1A depletion is hard to tell. In any case, we report a novel and contrasting difference between MLL and SETD1A in R-loop formation on the centromere. Our study also highlights the fact that despite being such well-studied co-activators of RNA Pol II, how different members of the MLL family regulate RNA Pol II, at various genomic loci, is still not clear.Due to our inability to generate SETD1A knock-out cells, we had to make use of SETD1A shRNA knock-down to interrogate the status of RNA Pol IIhromatin ,84. Anothromatin ,92. Theshromatin ,12. Prev2 in HAC . WhetherR-loops reported at centromeres have been proposed to be beneficial ,56,57 asHOXA-gene cluster through looping of chromatin in normal cells, failure of which could trigger leukemogenesis in mice. Another study reports that lnc RNA UMLILO interacts with MLL-WDR5 and imparts trained immunity in mice [Growing body of evidence suggests perturbed centromeric and pericentromeric transcription in pathological conditions like cancer ,95,96. F in mice . Here, wU-2OS (human osteosarcoma), HEK-293 (human embryonic kidney), and IMR-90 tert (human lung fibroblast) cells were grown as monolayers in DMEM, supplemented with 10% (v/v) fetal bovine serum (FBS), 1% (v/v) GlutaMAX, and 100 U/ml penicillin-streptomycin. The cells were maintained at 37°C in a humidified atmosphere with 5% CO2. All cell lines were authenticated by Lifecode Technologies Private Limited (India).MLL sgRNA were cloned into a lentiGuide-Puro vector, gift from Feng Zhang [U-2OS cells expressing MLL mutants have been described before  except Mng Zhang  in the Bng Zhang  was clonmll knock-out colonies were selected with 2 μg/ml Puromycin (Gibco). Several colonies were screened for loss of MLL protein expression through western blot and finally, 2 clones (MLL iKO #11 and MLL iKO #20) were selected for further analysis. Cas9 expression (and therefore MLL knockout) was induced with 5 μg/ml Doxycycline (Sigma) treatment for 7 days where the medium was replenished after every 3 days. For CENP A-SNAP experiments, pcDNA FRT-CENP A-SNAP-3xHA was transfected into U-2OS and MLL mutant cells lines, and selected in media supplemented with 200 μg/ml Hygromycin B. Similarly, the pcDNA 3.1-Puro-CENP A-SNAP-3xHA construct was transfected into U-2OS and SETD1A mutant cell lines and selected using 4μg/ml Puromycin. Despite several attempts, we were unsuccessful in generating stable cell lines for pcDNA FRT-CENP A-SNAP-3xHA with MLLΔTAD. Therefore, pcDNA FRT-CENP-A-SNAP-3xHA vector was transiently transfected into MLLΔTAD cell line 12 h before siRNA transfection and assay was performed as depicted in Generation of MLL cell lines has been described previously . SETD1A RNAi was performed with synthetic siRNA duplexes using Oligofectamine (Thermo Fischer Scientific) as previously described . The seqWhole-cell protein extracts were prepared by lysing cells in 2X NETN buffer , 1 mM EDTA, and 1% NP-40) supplemented with a freshly prepared protease inhibitor cocktail (Sigma) and boiled for 10 min. Equal amounts of protein extracts were resolved by SDS-PAGE and transferred to either PVDF or nitrocellulose membrane. Immunoblotting was performed with the following antibodies: MLL ; SETD1A ; CENP-A ; CENP-B , CENP-C , HJURP , HA , and α-tubulin . After probing with relevant secondary antibodies, blots were developed using Amersham ECL substrate or digital imaging using LI-COR Biosciences as described .Cells  used for immunofluorescence were grown on coverslips. Cells were arrested with nocodazole (100 ng/ml) treatment for 12 to 16 h and released into fresh medium for 60 min (mitotic cells) or 90 min (early G1), before fixing. Cells were fixed with freshly prepared 1% paraformaldehyde for 10 min at room temperature followed by permeabilization with 0.2% Triton X-100/PBS for 10 min. For staining RNA-DNA hybrids, cells were fixed and permeabilized with 100% ice-cold methanol for 10 min followed by acetone for 1 min on ice. Following fixation, immunofluorescence staining protocol was followed as described earlier . The samChIP was performed as described previously ,60. BrieFor both kinds of ChIP experiments, 1/10th of the fragmented chromatin was taken aside as input. The following antibodies were used for ChIP experiments: H3K4me2 ; H3K36me2 ; H3K9me3 ; H3K9Ac , MLL , SETD1A , total RNA polymerase II ; RNA polymerase IIS2P ; CENP-A , CENP-B , CENP-C , and IgG . After incubation with primary antibodies overnight at 4°C followed by the addition of Protein A or G Sepharose beads  for 2 to 3 h, immunoprecipitated material was washed with ChIP wash buffers. Immunoprecipitated and input DNA were subsequently purified using standard phenol, chloroform, and isoamyl alcohol extraction. The relative occupancy or percent input of the immunoprecipitated protein at each DNA locus was estimated by RT-qPCR as follows: 100 × 2(Ct Input–Ct IP), where Ct Input and Ct IP are mean threshold cycles of RT-qPCR on DNA samples from input and specific immunoprecipitations, respectively. To measure fold over control, fold change over the ChIP values obtained in the control cells was used. The primer sequences are listed in DNA DNA:RNA hybrids immunoprecipitation (DRIP) was performed as described earlier , 105 witTotal RNA isolation and cDNA preparation was made as described earlier . BrieflySNAP quench-pulse labeling was performed as described earlier  with theExtended chromatin fiber assay was performed as described ,107 witht test and two-way ANOVA were performed as mentioned in the legends. In two-way ANOVA, significance is calculated against mean of control versus mean of test (or IgG). Error bars represent standard error of the mean (SEM) or standard deviation (SD) wherever mentioned in the legends. For exact number of cells and experiments, please refer to figure legends.GraphPad Prism 9.3 software was used to perform statistical analysis. Student https://github.com/FelixKrueger/TrimGalore). Trimmed sequencing reads were mapped to the human reference genome (GRCh38) using STAR (v. 2.7.10a) [P-values were adjusted using Benjamini–Hochberg method, and the genes with adjusted P-value <0.05 and a fold change of 1.0 were identified as DEGs.Total cellular RNA was isolated either from Control, MLL, or SETD1A siRNA-treated cells using TRIzol (Ambion). Libraries for RNA-Seq were prepared using NEB Ultra II RNA Directional Library kit. Paired-end sequencing (2 × 150 bp) was performed on Illumina NextSeq 2000 at the sequencing facility—National Genomics Core (NGC), CDFD. The raw sequencing read pairs were trimmed by removing adapters using TrimGalore (v 0.6.7) (2.7.10a) . BAM fil2.7.10a) . Read co2.7.10a) . DESeq2,2.7.10a) . P-valuePathway and gene ontology analysis was performed using DAVID , a web server for functional annotation and enrichment analyzes of gene lists . CentromS1 FigA) siRNA-mediated down-regulation of various MLLs was performed and the efficacy of siRNA treatment was determined by plotting the qRT-PCR analysis of respective transcript levels after total RNA extraction and cDNA synthesis. (B–E) Immunoblots of whole-cell lysate were prepared from cells treated with either control and MLL (B), MLL2 (C), SETD1A (D), or SETD1B (E) siRNA to analyze the respective protein levels. Blots were probed with α-MLLC (B), α-MLL2 (C), α-SETD1A (D), and α-SETD1B (E) and α-tubulin as shown. Molecular weight markers (in kDa) and relative quantification are shown as indicated. Uncropped blots provided in F) cDNA samples obtained after RNAi treatment of Control, MLL2, MLL3, and SETD1B (from A) were analyzed for cenRNA transcripts from D17Z1, D17Z1-B, and D17Z1-C α-satellite arrays of chromosome 17. (G) qRT-PCR analysis of α-satellite cenRNA from individual HOR of chromosome 17 and RNA Pol II regulated gene PAX3, after treatment with either control (DMSO), Triptolide (20 μm), CDK9 inhibitor (20 μm), α-amanitin (20 μg) for 4 h, is shown.  cDNA was synthesized from total RNA after rigorous DNase I treatment and amplified using qRT-PCR for indicated RNAs. Data from all samples were normalized to GAPDH mRNA levels from respective samples by using − ΔΔCT method and expression is shown relative to control siRNA-treated/DMSO-treated cells from respective cell line/treatment (which is arbitrarily set to 1). Each experiment was performed at least 3, or more times except α-amanitin treatment (2 times). Error bars represent SD. *P ≤ 0.05, **P ≤ 0.005, ***P ≤ 0.0005, ****P ≤ 0.0001, ns: not significant, P > 0.05 (two-tailed Student’s t test). (H) Schematic representation of recombinant MLL and SETD1A FLAG-epitope tagged mutants used in this study displaying different domains in these proteins. Full-length MLL (FL) and SET domain deleted MLL (Δaa3829–3969) U-2OS cell lines have been described before [I. (I) siRNA resistant full-length SETD1A was generated by introducing 7 silent mutations (shown in red) at wobble positions between nucleotide +2916 to +2934 (Accession no NM_014712.3) in the full-length construct using site-directed mutagenesis. The siRNA (siRNA#1) sequence is underlined. CDK9i, CDK9 inhibitor; AT hook, AT-rich region; F, FLAG epitope tag; PHD, Plant homeodomain; Zn CXXC, Zinc-finger domain; Bromo, Bromodomain; RRM, RNA recognition motif; FYRN/C, Phenylalanine and tyrosine-rich region N-terminal/C-terminal; Win, WDR5 interacting motif. The raw data underlying parts (A) and  can be found in (d before . MLLΔTAD(TIF)Click here for additional data file.S2 FigA) Immunofluorescence staining (IF) of endogenous MLL (green) or SETD1A (green) with CENP-A (red) in U-2OS cells in interphase is shown. DNA was stained with DAPI (blue). The area in the white square is magnified and shown on the right for each image. (B) A 3D view of endogenous MLL (green) upper panel or SETD1A (green) lower panel. with CENP-A (red), is shown. The magnified area of the 3D model is shown on the right. (C-D) U-2OS cells were transfected with Control, MLL (C), or SETD1A (D) siRNA to check for the specificity of MLL or SETD1A staining at the centromere. Cells were stained with endogenous MLL (green) or SETD1A (green) with CENP-C (red) or CENP-A (red), and DNA was stained with DAPI (blue) as indicated. (E) U-2OS cells, stained with Alexa Flour 488 and Alexa Flour 594, are shown. (A–E) Scale bar, 5 μm. (F) U-2OS cells were stained with MLL2 (green), MLL3 (green), or SETD1B(green) antibody along with centromeric marker CENP-A (red) as shown. The area in the white square is magnified and shown on the left for each image. Scale bar, 2 μm.  Immunoblot show MLL (G) and SETD1A (I) shRNA (#1 and #2) knockdown efficiency in treated HEK-293 cells. The blots were probed with α-MLL (G) or α-SETD1A (I), and α-α-tubulin antibody. Uncropped blots provided in H, J) Chromatin immunoprecipitation (ChIP) analyzes showing decrease in levels of MLL (H) and SETD1A (J) at centromeric α-satellite loci following treatment of either MLL shRNA or SETD1A shRNA in HEK-293 cells, and the result plotted as percent input enrichment, are shown. Each experiment was performed at least 3 or more times. Error bars represent SD. *P ≤ 0.05, **P ≤ 0.005, ***P ≤ 0.0005, ****P ≤ 0.0001, ns: not significant, P > 0.05 (two-tailed Student’s t test). (K) CENP-B occupancy, detected by ChIP, is shown. Data from 3 or more independent ChIP experiments is shown. Error bars represent SD. *P ≤ 0.05, **P ≤ 0.005, ns: not significant, P > 0.05 (two-way ANOVA with Šídák multiple comparison test). α-sat, α-satellite. The raw data underlying parts (H) and  can be found in ((TIF)Click here for additional data file.S3 FigA) Cell cycle profile obtained from flow cytometry analysis of MLL KO (iKO #11 and #20) cells after 7 days of Doxycycline treatment is shown. Representative graph (from 3 independent experiments) is shown with values obtained for sample shown here. Parental (or Cas9-expressing) cells are used as Control. The raw data underlying this part can be found here (http://flowrepository.org/id/FR-FCM-Z6AH). (B–F) ChIP-analyzes with MLL (B), H3K4me2 (C), H3K9ac (D), H3K9me3 (E), and H3K36me2 (F) antibodies in MLL iKO cells (#20) are shown. Data were normalized against the ChIP values obtained in parental (or Cas9-expressing) cells, which are used as Control. Data from 3 or more independent ChIP experiments are plotted. Error bars represent SD. *P ≤ 0.05, **P ≤ 0.005, ***P ≤ 0.0005, ****P ≤ 0.0001, ns: not significant, P > 0.05 (two-way ANOVA with Šídák multiple comparison test). α-sat, α-satellite. The raw data underlying parts (B–F) can be found in ((TIF)Click here for additional data file.S4 FigA) Representative images for the data represented in B) DRIP analysis in MLL RNAi-treated HEK-293 cells, with respective RNase H controls, is shown. Data are presented as percent input enrichment. Data from 3 or more independent DRIP experiments are plotted.  DRIP analysis in HEK-293 cells, with asynchronous or cells synchronized in mitosis, is shown. Data are presented as percent input enrichment. Data from 3 or more independent DRIP experiments are plotted. Data from D is replotted in C for Control cells to highlight the changes observed in mitosis. Error bars represent SD. **P ≤ 0.005, ***P ≤ 0.0005, ns: not significant, P > 0.05 (two-way ANOVA with Šídák multiple comparison test).  Immunofluorescence staining of Total RNA Pol II  or RNA Pol IIS2P and CENP-A (red) in mitotic cells following treatment with either Control, MLL, or SETD1A siRNA, are shown. Scale bar, 5 μm. (G–I) ChIP-analysis of RNA Pol II (G) and RNA Pol IIS2P (H) in MLL knock out (iKO #11) and H3K4me2 (I) in SETD1A shRNA treated HEK-293 cells is shown. Data were normalized against the ChIP values obtained in Control samples and presented as fold change over control. Data from 3 or more independent experiments were plotted. Error bars represent SD. *P ≤ 0.05, **P ≤ 0.005, ****P ≤ 0.0001, ns: not significant, P > 0.05 (two-way ANOVA with Šídák multiple comparison test). Ctrl, control; si, siRNA; Asyn, asynchronous. The raw data underlying parts (B–D) and (G–I) can be found in ((TIF)Click here for additional data file.S5 FigA, B) U-2OS cells were either treated with Control, MLL (A), or SETD1A (B) siRNA, and immunoblots of whole-cell lysate showing MLL (A), SETD1A (B), and respective tubulin level are shown. Uncropped blots provided in A) or SETD1A (B) siRNA-treated cells were listed  GO enrichment analysis of differentially regulated transcripts were identified in MLL (C) and SETD1A (D) siRNA-treated cells. Biological processes of GO terms were ranked based on the adjusted p-value obtained from online web server DAVID. Ten most significant enriched GO terms are presented. The color represents padj value and the diameter of the circle size indicates no of genes in that category.  Venn diagram showing the overlap between the gene ontology annotations related to cell cycle, centromere, and transcription by RNA Pol II among DEGs in MLL-KD (E) and SETD1A-KD (F)  SETD1A siRNA-treated cDNA samples were analyzed for CENP-H transcript levels as shown. (H) cDNA samples obtained after RNAi treatment of Control, SETD1A, and MLL, were analyzed for CCTT lncRNA transcripts levels.  *P ≤ 0.05, **P ≤ 0.005, ns: not significant, P > 0.05 (two-tailed Student’s t test). SET1, SETD1A; up/down, up-regulated/down-regulated genes; GO, Gene Ontology; DEGs, differentially expressed genes; CCTT, CENP-C targeting transcript. The raw data underlying parts  can be found in  also see  Tables. (TIF)Click here for additional data file.S6 FigA–D) Immunoblot shows CENP-C (A), CENP-B (B), HJURP (C), and CENP-A (D) protein levels in Control or MLL siRNA-treated U-2OS cells. (E–H) Immunoblot shows CENP-C (E), CENP-B (F), HJURP (G), and CENP-A (H) protein levels in Control or SETD1A siRNA-treated U2OS cells. (I–L) Immunoblot analysis of CENP-C (I), CENP-B (J), HJURP (K), and CENP-A (L) protein levels in MLL HEK-293 KOs (iKO #11 and #20) cell lines are shown. Blots were probed with respective antibodies as indicated. Molecular weight markers (in kDa) are shown on the left and quantitative analysis of respective protein levels from 2 independent experiments is shown on the right. Each bar represents mean SD. **P ≤ 0.005, ns: not significant, P > 0.05. . Uncropped blots provided in A–L) can be found in ((TIF)Click here for additional data file.S7 FigA) Quantification of HJURP fluorescence intensity following depletion of Control, MLL, SETD1A, or MLL+SETD1A. Each data point represents a single centromere. Quantification of HJURP fluorescence images shown in Fig 6G) The error bar represents SEM ≥250 centromeres quantified from 10 early G1 cell pairs, (n = 3 experiments). ****P ≤ 0.0001, *P ≤ 0.05, ns: not significant, P > 0.05 (Ordinary one-way ANOVA with Tukey’s multiple comparisons test). (B) Quantification of centromeric fluorescence intensity of ectopically expressed total CENP-A (stained using α-HA antibody) in parent U-2OS cells (—) or cell line stably expressing MLL full length (FL) or MLLΔTAD or MLLΔSET upon MLL siRNA treatment. (C) Quantification of centromeric fluorescence intensity of total CENP-A in parent U-2OS cells (—) or cell line stably expressing siRNA resistant SETD1A full length (FL) or SETD1AΔSET  upon SETD1A siRNA. Each data point represents a single centromere; n ≥ 300 quantified from 10 early G1 cell pairs, (n = 2 experiments). ****P ≤ 0.001, ns: not significant, P > 0.05 (Mann–Whitney two-tailed unpaired test).  Stably expressing CENP-A SNAP-3xHA cells were either transfected with Control, MLL (D), or SETD1A (E) siRNA, and collected after 72 h for whole-cell lysate preparation. CENP-A-SNAP-3xHA protein was detected using an α-HA antibody. Uncropped blots provided in P ≤ 0.05, ns: not significant.  Immunofluorescence staining (IF) of chromatin fiber prepared from cell line stably expressing MLLΔSET (F) or SETD1AΔSET . Stably cell line cells were transfected either with Control, MLL siRNA (F), or SETD1A (G) siRNA and the chromatin fibers were extracted and stained with endogenous CENP-A (green) and H3K4me3 (red), and DNA stained with DAPI (blue). (F) Frequency of H3K4me2 co-localizing with CENP-A was found to be 12/15 in Control. This dropped to 5/28 upon MLL siRNA treatment. (G) Frequency of H3K4me2 co-localizing with CENP-A was found to be 8/8 in Control and 0/6 upon SETD1A siRNA treatment. Scale bar, 10 μm. The raw data underlying parts (A–E) can be found in ((TIF)Click here for additional data file.S1 Methods(DOCX)Click here for additional data file.S1 Table(XLS)Click here for additional data file.S2 TableList of differentially expressed genes upon MLL and SETD1A knockdown for GO term—Cell Cycle.(XLS)Click here for additional data file.S3 TableList of differentially expressed genes upon MLL and SETD1A knockdown for GO term—transcription by RNA Pol II.(XLS)Click here for additional data file.S4 Tablep values represent qRT PCR validation of same genes.Selected genes involved in CENPA deposition were analyzed upon MLL and SETD1A knockdown and results were compared to data obtained by RNA-Seq analysis shown in (XLSX)Click here for additional data file.S1 Data(XLSX)Click here for additional data file.S1 Raw Images(PDF)Click here for additional data file. 25 Jul 2022Attachment126050_1_rebuttal_2388117_rdnql9.docxSubmitted filename: Click here for additional data file. 2 Aug 2022Dear Dr Tyagi, Thank you for submitting your Review Commons manuscript entitled "MLL family members regulate H3K4 methylation to ensure CENP-A assembly at human centromeres." for consideration as a Research Article by PLOS Biology. 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In addition, for the revised version to be a strong candidate for publication, the Academic Editor would like you to consider potential indirect explanations for the role of MLL and SETD1A in centromere transcription and centromere biology. Please see the comments below from the Academic Editor regarding this point.We cannot make any decision about publication until we have seen the revised manuscript and your response to the reviewers' comments at Review Commons. Your revised manuscript is also likely to be sent for further evaluation by the original reviewers.plosbiology@plos.org) if you have any questions or concerns, or would like to request an extension. At this stage, your manuscript remains formally under active consideration at our journal; please notify us by email if you do not intend to submit a revision so that we may end consideration of the manuscript at PLOS Biology.We expect to receive your revised manuscript within 3 months. 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Read more information on sharing protocols at Thank you again for your submission to our journal. We hope that our editorial process has been constructive thus far, and we welcome your feedback at any time. Please don't hesitate to contact us if you have any questions or comments.Sincerely,RichardRichard Hodge, PhDAssociate Editor, PLOS Biologyrhodge@plos.org------------------------------------Comments from the Academic Editor:This paper implicates MLL (KMT2) and SetD1A in affecting various aspects of centromere biology. Given the diverse roles for these proteins in the gene expression programs across the cell, a major challenge for this paper is determining whether the phenotypes observed following depletion of these proteins reflect a direct role for these proteins at centromeres or whether these effects are indirect through altering gene expression more broadly. The localization of these proteins to centromeres does not exclude the possibility that the phenotypes resulting from their depletion can be explained by gene expression changes. This is a critical point that the author's need to address directly both through experiments and changes to the text.For example, prior work has suggested that centromere proteins , ATR, 53BP1, cohesin, RNA Polymerase I, the nucleolus, and MANY other factors also influence centromere transcription. Thus, changes in the expression of any of these factors, their regulators, or many others have the potential to alter centromere transcription indirectly. The authors conduct Western blots and cite published gene expression data to suggest that there are not substantial changes in a selected number of centromere components . However, the data provided does not rule out these alternative explanations. In an ideal world, it would be valuable for the authors to provide robust RNA-seq data to evaluate the gene expression changes that occur in their knockdown conditions and in their cell types. They could also test some of these other possibilities more directly. In addition, even with these other controls, it is important that the authors be extremely cautious with their wording in the abstract, Results, and Discussion to highlight the multiple potential explanations and not to definitively state the conclusion that this reflects a direct role for MLL at centromeres. In addition to the experimental changes, this paper should include a clear acknowledgement of this potential alternative explanation and describe the limitations of their existing study and data. 9 Mar 2023AttachmentResponse to Reviewers.pdfSubmitted filename: Click here for additional data file. 18 Apr 2023Dear Dr Tyagi,Thank you for your patience while we considered your revised manuscript "MLL family members regulate H3K4 methylation to ensure CENP-A assembly at human centromeres" for publication as a Research Article at PLOS Biology. Please accept my apologies for the delays that you have experienced during this round of the peer review process. This revised version of your manuscript has been evaluated by the PLOS Biology editors, the Academic Editor and three of the original reviewers at Review Commons.In light of the reviews, which you will find at the end of this email, we are pleased to offer you the opportunity to address the comments from the reviewers in a revision that we anticipate should not take you very long. After discussions with the Academic Editor, we will not make the inclusion of additional experimental data a requirement for publication, but we do ask that the comments are fully addressed by caveating the limitations of the work in the manuscript text and discussing possible alternative explanations for the data. We will then assess your revised manuscript and your response to the reviewers' comments with our Academic Editor aiming to avoid further rounds of peer-review, although might need to consult with the reviewers, depending on the nature of the revisions.In addition, I would be grateful if you could please address the following data and other policy-related requests that I have provided below (A-H):(A) We would like to suggest the following modification to the title:“MLL methyltransferases regulate H3K4 methylation to ensure CENP-A assembly at human centromeres”http://journals.plos.org/plosbiology/s/data-availability. For more information, please also see this editorial: http://dx.doi.org/10.1371/journal.pbio.1001797(B) You may be aware of the PLOS Data Policy, which requires that all data be made available without restriction: Note that we do not require all raw data. Rather, we ask that all individual quantitative observations that underlie the data summarized in the figures and results of your paper be made available in one of the following forms:-Supplementary files . Please ensure that all data files are uploaded as 'Supporting Information' and are invariably referred to  using the following format verbatim: S1 Data, S2 Data, etc. Multiple panels of a single or even several figures can be included as multiple sheets in one excel file that is saved using exactly the following convention: S1_Data.xlsx (using an underscore).-Deposition in a publicly available repository. 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We ask that you notify us as soon as possible if you or your institution is planning to press release the article.*Protocols deposition*https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocolsTo enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at Please do not hesitate to contact me should you have any questions.Kind regards,RichardRichard Hodge, PhDAssociate Editor, PLOS Biologyrhodge@plos.org------------------------------------------------------------------------Reviewer remarks:Reviewer #1: The authors have satisfactorily addressed all concerns raised.Reviewer #3: This is a revised manuscript from Malik and colleagues examining the role of MLL and SetD1A in centromere specification and transcription. Overall, the revisions have improved the manuscript, and most of the issues that were raised previously have been addressed. I think the weakness of the manuscript is that the data show that MLL and SetD1A influence centromeric transcripts, but the experiments do not demonstrate that the centromeric transcripts are the mechanism by which CENP-A and HJUPR recruitment are altered in MLL and SetD1A knockdown. But I will stipulate that this may be difficult to directly demonstrate, and I do not think they have been sufficiently proven in the literature. It is very interesting that the data suggest that SetD1A and MLL may be functioning differently, as SetD1A alters CENP-H and CCTT expression, both of which influence CENP-A deposition (see Okada 2006). The manuscript incorrectly states that CENP-H does not influence CENP-A deposition, however, Okada et al 2006 showed otherwise. The data that show SetD1A + MLL knockdown have a more drastic phenotype is excellent to see in the manuscript and solves of the big issues I had with the original manuscript, which was why do Set1DA and MLL both show phenotypes. However, it should be noted that despite the statement on page 19, "Our observations indicate that both MLL and SETD1A contribute to CENP- A recruitment synergistically." there is no data for synergy, which would require additional analysis. However, they could very well be additive, which is consistent with altering multiple pathways. One last point is that the analysis of the transcriptional changes is insufficient to dispel the concern that MLL is altering transcription of upstream regulators of CENP-A deposition. Besides HJURP, CENP-C and CENP-A there are many other genes that could negatively alter CENP-A deposition. At the very least, the transcriptional effects of SetD1A and MLL should be shown for Mis18a, Mis18b, Mis18BP1, CENP-I and PLK1. There are others suggested in the literature as well, and the authors should make an effort to pick these out of the RT PCR data to show whether they are changed.Reviewer #4: Major commentBy the addition of control and/or double knockdown experiments in each revised figure, datasets are now comparable and easier to understand than before. In addition, the title was changed to focus solely on functional link between endogenous centromere H3K4me2 transferase and nascent CENP-A assembly mechanism. Data on the involvement of SET domain in the CENP-A assembly mechanism is also added, and supported conclusion of the title. The manuscript had been improved.Minor commentsSince the double knockdown of MLL and SETD1A synthetically reduced nascent CENP-A assembly , unique properties of both MLL and SETD1A, such as the different PolII or R-loop regulation manner, might also be involved in nascent CENP-A assembly. If the functional link between the PolII or R-loop regulation and nascent CENP-A assembly is investigated, the Figure 4 will fit the manuscript more tightly.In the Figure 7G, how can the authors identify which fiber is centromere? And, how frequent can the authors observe such the events per centromere fiber? If the authors add the results of fiber imaging, number or frequency of the events should be shown. 8 May 2023AttachmentResponse to Reviewers.docxSubmitted filename: Click here for additional data file. 12 May 2023Dear Shweta,On behalf of my colleagues and the Academic Editor, Iain Cheeseman, I am pleased to say that we can accept your manuscript for publication, provided you address any remaining formatting and reporting issues. These will be detailed in an email you should receive within 2-3 business days from our colleagues in the journal operations team; no action is required from you until then. 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HLA-I) genotype with oncogenic mutational profile and immunotherapy efficacy, we aimed to assess whether differential HLA-I genotype could predict the postoperative outcomes in resected PAAD patients.Patients with resected pancreatic adenocarcinoma (PAAD) often experience short-term relapse and dismal survival, suggesting an urgent need to develop predictive and/or prognostic biomarkers for these populations. Given the potential associations of the human leukocyte antigen class I  genotyping and somatic variants of 608 Chinese PAAD patients were determined by targeted next-generation sequencing of matched blood cells and tumor tissues. HLA-A/B alleles were classified with the available definition of 12 supertypes. The Kaplan–Meier curves of disease-free survival (DFS) and multivariable Cox proportional-hazards regression analyses were performed to determine the survival difference in 226 selected patients with radical resection. Early-stage (I–II) patients constituted the majority  and some stage I–II individuals with high-quality tumor samples were analyzed by RNA-sequencing to examine immunophenotypes.+B62+B44− had significantly shorter DFS  than patients without this genotype. Notably, stage I–II patients carrying HLA-A02+B62+B44− had sharply shorter DFS than those without HLA-A02+B62+B44− . Multivariate analysis revealed that HLA-A02+B62+B44− was associated with significantly inferior DFS (P=0.014) in stage I–II patients but not in stage III patients. Mechanistically, HLA-A02+B62+B44− patients were associated with a high rate of KRAS G12D and TP53 mutations, lower HLA-A expression, and less inflamed T-cell infiltration.Patients with HLA-A02+B62+B44−, was a potential predictor for DFS in early-stage PAAD patients after surgery.The current results suggest that a specific combination of germline HLA-A02/B62/B44 supertype, HLA-A02  HighlightsHLA-I) genotypes negatively impact disease-free survival (DFS) in resected pancreatic adenocarcinoma (PAAD).Specific human leukocyte antigen class I  as well as main driver gene alterations  are associated with worse postoperative outcomes in PAAD patients4. The serum level of CA 19-9 is the only approved and extensively used noninvasive biomarker to monitor the disease recurrence after surgical resection. However, it is unclear why some early-stage (I–II) PAAD patients with normal CA 19-9 level (<37 U/ml) also experience short-term relapse and inferior postoperative survival, suggesting that there is an urgent need to develop robustly predictive and/or prognostic biomarkers for patients with resected PAAD.PAAD is one of the most lethal causes of cancer mortality around the world. Although surgery is the curative treatment for most early-stage PAAD patients, the postsurgical recurrence rate within 1 year was above 50% and the 5-year survival rate was under 30%HLA-I genotype-restricted immunoediting has been described in various solid tumors where recurrent oncogenic mutations tend to have poor HLA-I presentation5. It could shape the personalized mutational profile and mediate the immune escape during tumorigenesis via impairing antigen presentation in an oncogenic-dependent manner5. Given the abundant genetic polymorphism of HLA genes , it is hypothesized that each cancer patient carrying distinctive HLA alleles is gifted with a differentiated efficiency of antigen presentation, possibly resulting in different therapeutic response or clinical outcome. Previously, HLA-B44 or B62 supertype (clustered HLA molecules with similar antigen binding specificity) was reported to be associated with better or worse survival in melanoma patients following checkpoint blockade immunotherapies6. Nevertheless, whether HLA-I genotypes could influence postoperative outcomes in patients with early-stage cancers remains largely unknown.HLA-I genotypes could impact the disease recurrence for patients with early-stage PAAD after radical pancreatectomy. Herein, we analyzed somatic variants and the profiles of HLA-I  alleles and their supertypes in 608 PAAD patients with matched blood cells and carcinoma tissues. Then, 226 individuals undergoing radical pancreatectomy were selected to evaluate the associations between HLA-I genotypes and postoperative survival outcomes. We also performed data validation in an independent cohort of long-term survivors  with PAAD versus those resected PAAD patients with early recurrence and multiple public cohorts of PAAD patients. Moreover, targeted transcriptomic sequencing of some high-quality PAAD tumor tissue samples was conducted to investigate the potential explanations for the associations between specific HLA-I genotypes and postoperative outcomes.In this study, we hypothesized that specific N=226), 202 patients (89.4%) received adjuvant therapy; the other 24 patients did not receive adjuvant therapy because of objective or subjective reasons, mainly due to age, low physical strength score, postoperative complications, poor nutrition status, or psychological factors. All adjuvant therapies followed the standard regimen (based on gemcitabine or 5-fluorouracil for 6 months) recommended in the guidelines, and there were no patients receiving neoadjuvant therapy or immunotherapy among them. The patients with nonradical resections or the postsurgical relapse-free individuals with follow-up less than 6 months were excluded from the survival analysis. DFS was defined as the time between surgical resection and disease relapse. The flowchart of patients’ selection is shown in Figure N=42) with more than 5-year survival after surgery as well as some early-stage PAAD patients (N=78) with very short-term recurrence within 6 months after radical resection were used for validation. Cancer staging was based on the American Joint Committee on Cancer (AJCC) eighth edition of TNM staging system. This study  was approved by the Medical Ethical Committee of the Hospital and performed in accordance with relevant guidelines. The work has been reported in line with the STROCSS criteria7  and was registered in ClinicalTrials.gov .Our discovery cohort included 608 Chinese individuals pathologically diagnosed with PAAD from a genetic testing database or the Hospital between 14 March 2018, and 26 April 2020. All patients signed an informed consent form before this study. Among 608 patients, 226 of them  undergoing radical pancreatectomy (R0) in the hospital were selected for survival analyses of DFS and their clinicopathological parameters  were collected from this hospital. In this cohort (HLA-A/B/C) at a CAP-certified laboratory or in the Hospital. DNA libraries were captured by HyperCap Target Enrichment Kit (Roche) and sequenced on the instruments of Illumina Novaseq. 6000 or NextSeq CN500. The average deduped sequencing depths of tissues and blood cells were ×830 and ×240, respectively. More details of sequencing and data analyses pipeline were described in the Supplementary Methods .Tumor tissue specimens and matched peripheral blood cells underwent next-generation sequencing targeting 543 or 769 cancer-related genes  genes were extracted from those BAM files of blood cells and then imported into software HLA-HD (v1.2.0.1)8 to identify HLA-I alleles with the following parameters: minimum_tag_size=50, rate_of_cutting=0.95. HLA-A/B alleles were classified with the available definition of supertypes like previously described9. Unsupervised clustering of HLA-A/B supertypes was performed using the Partitioning Around Medoid algorithm and distance was calculated via euclidean metric in the R package ConsensusClusterPlus. And R package ComplexHeatmap was used to display the clustering results.Reads in regions of 10. RNA of tumor tissue specimens was extracted using truXTRAC extraction kit (Covaris). Quantification of isolated RNA was performed using Qubit RNA HS Assay Kit (Thermo Fisher Scientific) and then reversely transcribed into complementary DNA. RNA libraries were prepared by amplification with specific primers targeting 395 genes and sequenced on the Ion Torrent S5 Systems according to the manufacturer’s instructions. Gene expression was initially calculated as reads per million (RPM) and the normalization ratio determined by RPM of 10 housekeeping genes was used to normalize RPM counts for each gene in the examined samples. And the differential expression genes were identified through R package limma with a P-value less than 0.05 and abs(log2fold change) more than 1. The immune-related signatures or markers examined in this study were listed as follows: Activated CD8 T cell11, type 1 T helper (Th1) cell11, T-cell–inflamed gene expression profile 13, T-cell markers 14, IFN-γ signature 12, Monocyte11. ssGSEA scores of these signatures were calculated by R package GSVA16.Expression levels of immune-related genes, signatures, or markers were determined by Oncomine Immune Response Research Assay , an RNA-based next-generation sequencing assay targeting 395 genes like previously describedP-value less than 0.05 denoted statistical significance.The Kaplan–Meier curves generated by GraphPad Prism 8.0 were used to estimate differences in DFS among grouped patients by a two-sided log-rank (Mantel–Cox) test. Stratified multivariable Cox proportional-hazards regression models were used to examine multivariable effects of identified germline HLA-A02/B62/B44 supertype combinations, clinical characteristics, and somatic alterations on DFS through the R packages survival and survminer. The statistical differences of above immune-related signatures or markers revealed in the boxplot were calculated by the R package ggpubr using the Wilcoxon test. The Spearman rank correlation test was used for assessing the correlations between HLA-A02/B62/B44 supertype combination or single supertype and common driver mutations or genetic alterations of oncogenic pathways. Fisher’s exact test or chi-square test was applied to compare the differences of categorical variables. All statistical tests were two-sided unless denoted otherwise. HLA-A, HLA-B, and HLA-C alleles  were called in 608 PAAD patients, and 99 HLA-A/B alleles were assigned to 12 disparate supertypes with the available definition9, based on their peptide-anchor-binding specificity17. The top 10 HLA-A/B alleles and corresponding supertypes were listed in Figures P=0.0001) in the same subgroup of patients, whereas HLA-B44 supertype was inclined to be mutually exclusive with A02 or B62 supertype  by their innate combinations of HLA-A02/B62/B44 supertypes as depicted in Figure In total, 133 individual HLA-A/B/C alleles and according to supertypes in 226 individuals were consistent with that observed in 608 patients . Intriguingly, patients with HLA-A02+B62+B44− had significantly shorter DFS  than patients without this genotype . Importantly, stage I–II patients (N=185) carrying HLA-A02+B62+B44− had sharply shorter DFS than other early-stage patients   . The improved separation of survival curves in stage I–II individuals may be on account of the rationale that HLA-based immunoediting takes effect predominantly in the early phase of tumorigenesis5. It should be noted that the patients harboring B62+B44− had obviously inferior survival compared with patients with B62−B44+ in A02-positive individuals . Furthermore, the significant difference of DFS between those patients with HLA-B44 supertype or not  was observed in extremely early-stage (IA–IB) individuals (N=86) . It seemed that B44 supertype was likely a favorable prognostic factor for early PAAD and B62 supertype was the opposite, which was akin to the positive or negative effect of B44 or B62 supertype on survival in melanoma cohorts with checkpoint blockade immunotherapy6. But these two supertypes were almost required to be combined with A02 supertype to reach the statistical significance for univariate survival analyses in the whole cohort and some subgroup .To reduce the potential bias produced by different surgical margin status affecting postoperative survival, we selected 226 individuals received radical pancreatectomy (R0) in a single center to perform Kaplan–Meier analyses. Their clinical characteristics were presented in Table +B62+B44− could help to identify patients with worse outcomes   with preoperative normal CA 19-9 (≤37 U/ml) who are generally believed to possess relatively better prognosis than their counterparts, whereas there was no significant statistical difference on DFS between HLA-A02+B62+B44− or not in high-CA 19-9 (>37 U/ml) patients (N=158) . In addition, stage I–II patients with HLA-A02+B62+B44− and preoperative high level of CA 19-9 had a higher 6-month relapse rate than those with a low level of CA 19-9 and without HLA-A02+B62+B44−  .Notably, HLA-A02+B62+B44−. Among all patients, HLA-A02+B62+B44− was a potential risk factor with marginal statistical significance , while pN stage, differentiation, and adjuvant therapy had a significant impact on DFS  . Moreover, HLA-A02+B62+B44− was associated with shorter DFS in patients with low level of CA 19-9 , which was superior to other prognostic factors . Collectively, HLA-A02+B62+B44− was a potential predictor of disease recurrence in PAAD patients after radical surgeries, especially in patients with early-stage or low CA 19-9 level.Then, we performed multivariable Cox proportional-hazards regression analyses  to further explore the independent prognostic role of HLA-A02DFS Fig. D. In pat+B62+B44−, we performed germline HLA-I genotyping of two independent cohorts: cohort 1 included stage I–II PAAD patients (N=42) with radical pancreatectomy and survived over 5 years since surgery ; cohort 2 included early-stage PAAD patients (N=78) who relapsed within 6 months  after radical surgery. In ER6 cohort, there were 39 patients with postoperative relapse in 3 months  and 39 relapsed during 3–6 months after surgery. Patients in ER3 cohort had higher rate of HLA-A02+B62+B44− or A02 than those in LTS5 cohort  . Importantly, a clear step-down of the patients carrying HLA-A02+B62+B44− or A02 supertype was observed from ER3/6 (early recurrence in 3 or 6 months) cohorts towards LTS5/6/7/8  cohorts in which there was only one individual with A02+B62+B44− in 15 patients surviving more than 8 years . In addition, there was a significant decrease of the frequency of A02 supertype among ER3 cohort, LTS7 cohort, and those patients with a survival of 5–7 years  , suggesting that specific unfavorable HLA-I genotypes may be negatively correlated with long-term survival of PAAD patients, particularly in those very long-term survivors (VLTSs).To validate the predictive value of HLA-A02+B62+B44− was associated with poor DFS in radically resected PAAD patients, we examined potential causes from two respects: mutational feature and gene expression. Given the generally low presentation of oncogenic alterations by HLA-I molecules18, we suspected that certain driver mutations might be further enriched in those individuals carrying unfavorable HLA-I genotypes. In effect, HLA-A02+B62+B44− and single B62 supertype were significantly correlated with TP53 mutations and/or KRAS G12D mutations , while no statistical correlations with other major mutated driver genes  or hotspot mutations (KRAS G12V/G12R) were observed in this analysis . In addition, the alterations of p53 pathway and/or Wnt pathway of 10 vital oncogenic signaling pathways19 were statistically associated with specific HLA-I genotypes . Considering the association of alterations in KRAS and TP53 with worse outcomes of resected PAAD patients like previously described20, reduced DFS of the individuals carrying HLA-A02+B62+B44− could be partly attributed to their augmented KRAS G12D and TP53 mutations. Notwithstanding, the A02 supertype alone was not found to be linked to any alterations of main driver genes or cancer-related pathways .To address why HLA-A02N=44) with available tissue specimens and well/moderate differentiation were selected from 226 PAAD patients to determine whether various HLA-I genotypes were implicated in differential immunophenotype of tumor microenvironment by RNA-sequencing10. As shown in Figure +B62+B44− (N=14) and others (N=30) were identified. Notably, the expression of HLA-A was markedly reduced in tumor tissues of HLA-A02+B62+B44− patients or A02-positive individuals relative to other cases , whereas there were scarcely any similar observations of other HLA encoding genes. Except for the A02 supertype, such dropped expression of HLA-A was absent between the patients with any other HLA-A supertypes or not. Even the individuals with HLA-A03 supertype had dramatically higher expression of HLA-A than that of those HLA-A03-negative individuals (P<0.001) . That is to say, the PAAD patients carrying HLA-A02 supertype rather than other HLA-A supertypes appeared to be more prone to have downregulated HLA-A, consequently facilitating immune evasion owing to lessened expression of HLA and impaired antigen presentation in cancer cells23, which was likely a contributory cause for short-term recurrence of HLA-A02+B62+B44− individuals infrequently observed in PAAD LTSs. Besides, HLA-B/C expression was obviously decreased in B44-negative versus B44-positive individuals or B62-positive versus B62-negative individuals . However, no marked difference of HLA-B/C expression was observed between HLA-A02+B62+B44− patients and other patients  in HLA-A02+B62+B44− patients than in other patients, whereas a significantly higher of TNFSF9 (tumor necrosis factor ligand superfamily member 9) was present in the former than in the latter  or B44-negative versus B44-positive individuals , respectively. Likewise, the expression levels of Activated CD8 T cell, Th1 cell, and other immune-related signatures or markers  exhibited a significant or considerable reduction in HLA-A02+B62+B44− or B44-negative patients compared to their counterparts . Accordingly, such unfavorable immunophenotype was likely more difficult to control cancer cells and eventually bring about poorer outcomes of the individuals with HLA-A02+B62+B44− relative to other individuals.In addition to 17 and without HLA-I genotyping data in TCGA (The Cancer Genome Atlas) or ICGC , co-mutant KRAS G12D and TP53 correlated with HLA-A02+B62+B44− was used as a derived genomic ‘indicator’ to test the prognostic significance of HLA-A02+B62+B44− for PAAD in public data. We found that PAAD patients with concomitant KRAS G12D and TP53 mutations indeed had even worse overall survival (OS) compared with other PAAD patients in both entire TCGA cohort (N=179)  and stage I–II PAAD patients (N=167) of TCGA cohort  . Likewise, the PAAD patients with KRAS G12D plus TP53 co-mutations had much shorter OS  than that of other PAAD patients in ICGC cohort (N=235) . Moreover, the prognostic effect of KRAS G12D and TP53 co-mutations was further strengthened  in stage I–II patients (N=160) of ICGC cohort . Apparently, it resembled our observed enhanced impact of HLA-A02+B62+B44− on DFS in early-stage PAAD patients relative to all patients  of OS between the patients with co-occurrence of KRAS G12D and TP53 mutations or not in a metastatic PAAD cohort24 (N=293) , which was similar to our observation that HLA-A02+B62+B44− failed to stratify in stage III patients with PAAD . Briefly, in accordance with the stage-specific influence of HLA-A02+B62+B44− on DFS in our cohort, its ‘indicator’ (co-mutant KRAS G12D and TP53) also had associations with poor survival of only early-stage but not late-stage PAAD patients in public cohorts.Finally, we performed validation of our findings in several public cohorts of PAAD. Given the ethnic difference of HLA-I supertypes between Chinese versus Western populationsHLA-I genotype, HLA-A02+B62+B44−, as a potential prognostic factor for DFS in PAAD patients with radical resections, especially in those stage I–II or low CA 19-9 (≤37 U/ml) individuals. Moreover, we noticed that HLA-A02+B62+B44− appeared to be negatively correlated with long-term survival in an independent cohort of PAAD LTSs (surviving more than 5 years since surgery) and early-stage PAAD patients with early relapse in 3 or 6 months. Correspondingly, HLA-A02+B62+B44−-related ‘indicator’ co-occurrence of KRAS G12D and TP53 mutations was verified to be significantly relevant to poor outcomes in stage I–II PAAD patients in both TCGA and ICGC cohort. Mechanistically, tumor with HLA-A02+B62+B44− seemed to be associated with increased KRAS G12D and TP53 mutations, attenuated antigen presentation, and antitumor immune response.In this study, we identified the specific 28. However, the extremely low abundance of ctDNA might hinder the application of ctDNA-based liquid biopsies in PAAD patients with radical resections. In comparison with ctDNA detection, HLA-I genotyping based on peripheral blood cells is easier to implement. Importantly, our data showed the relevance of HLA-A02+B62+B44− to poor DFS in early-stage, low CA 19-9, or well/moderate-differentiated PAAD patients. Perhaps enhanced therapy or follow-up visit rather than routine adjuvant therapy or follow-up visit is needed for the PAAD patients with HLA-A02+B62+B44−. In other words, HLA-I genotyping may be conductive to clinical decision-making of those resected PAAD patients with low risk evaluated by current prognostic parameters .According to recent NCCN guideline for PAAD, surveillance via radiological examination or CA 19-9 level should be performed every 3–6 months for 2 years after surgery, and adjuvant therapy is recommended for all patients unless they have poor performance status. Even so, postoperative relapse within one year and miserable outcomes are commonly found in stage I–II PAAD patients with low CA 19-9. How to identify certain individuals subject to recurrence remains troublesome for clinical management of resected PAAD. Some studies revealed the promising prognostic significance of perioperative circulating tumor DNA (ctDNA) superior to imaging or CA 19-9 results for PAAD6 and the prognostic role of HLA-A02* genotype (not A02 supertype) in epithelial ovarian cancer29, while the clinical significance of HLA-I supertype combinations in cancer patients is overlooked to a large extent so far. To our knowledge, this is the first study to investigate the impact of inherent HLA-A02/B62/B44 supertype combination on survival outcomes in patients with PAAD. The results demonstrated the potential meaning of HLA genetic background combined with clinical characteristics for predicting the prognosis of resected PAAD. It is noteworthy that both HLA-A02+B62+B44− and its ‘indicator’ KRAS G12D and TP53 co-mutations failed to exhibit prognostic significance in advanced or metastatic PAAD patients of our cohort or public cohort, which is likely owing to the widespread immunosuppression and ineffective immunoediting in late-stage PAAD than in early-stage PAAD30. Therefore, the alterations of major driver genes are perhaps not suitable to be used as universal biomarkers for evaluating outcomes of those PAAD individuals undergoing radical  or nonradical  resections like previously performed4. Many studies have shown the associations of alterations in four established driver genes  with clinical outcomes of resected PAAD patients31, whereas there seems to be no consensus about the well-defined concurrent mutations of driver genes (e.g. KRAS G12D and TP53 co-mutations) as prognostic biomarkers for stage-specific patients and it could be expanded by our observations. Enriched KRAS G12D and TP53 mutations were significantly correlated with HLA-B62 supertype but not A02 or non-B44 supertype in our results, indicating that potential neoantigens derived from these driver mutations might be more difficult to be presented in B62-positive patients than in others, which is in agreement with restrained neoantigen recognition of B62 supertype owing to innate structural features as shown by molecular dynamics stimulations6. More details of the interaction between various oncogenic alterations of PAAD and diverse HLA-I genotypes in different ethnic populations as well as their impact on prognosis remain to be elucidated in future studies.Prior studies reported the promising value of a single HLA-B62 or B44 supertype in predicting the efficacy of immunotherapy in melanoma33. Poor survival is closely related with typical early recurrence in PAAD patients following surgeries; nonetheless, why some patients with stage I–II PAAD received radical resections relapse shortly is still poorly understood. In principle, tumor relapse is mainly determined by two aspects: oncogenic genomic alterations of residual disease after surgical removal and antitumor response of individualized host immune system closely connected with HLA polymorphism. In addition to enrichment of certain driver mutations in HLA-A02+B62+B44− patients, special immunophenotype characterized by downregulation of HLA-A/TLR8 and upregulation of TNFSF9 was observed in these patients  function and enhance antitumor immunity37. In view of the prevalent Tregs-inducing immunosuppressive microenvironment in PAAD40, it makes sense that declining expression of TLR8 could aggravate the immunosuppression state due to Tregs and impede antitumor immune response by CD8 T cells and Th1 cells in HLA-A02+B62+B44− or B62-positive patients as shown in our results  of HLA-I likely lead to tumor immune evasion and immunotherapy failure23. Accordingly, based upon marked downregulation of HLA-A in A02-positive individuals versus A02-negative individuals as noted above, A02 supertype seems to facilitate short-term relapse in PAAD patients after surgery but hamper their long-term survival benefit. Indeed, it is in accordance with our observations that PAAD LTSs or VLTSs had even lower frequencies of A02 supertype or HLA-A02+B62+B44− than in those stage-matched PAAD patients with early recurrence. Typically, there were no A02 supertype alleles identified in a rare PAAD VLTS who carried HLA-A*11:01 allele of A03 supertype had survived over 14 years in the context of multiple surgeries and metastases across one decade45. More importantly, her primary and metastatic tumors were always governed by KRAS G12V mutations predicted to be neoantigens with strong affinity to HLA-A*11:01, while she did not have any other common immune-silent driver mutations in PAAD45. Therefore, it could be supposed to infer that specific neoantigens in combination with favorable HLA-I genotypes, but neither alone, bring about good postoperative outcomes of certain PAAD patients, which might provide enlightenment for therapeutic neoantigen vaccine development in cancer patients.Neoantigen-mediated immune response has been shown to be correlated with long-term survival of resected pancreatic cancerHLA-I genotypes for resected PAAD, there are still some limitations. Due to no independent cohort of resected PAAD patients with enough HLA-I genotyping information and survival data, we fail to directly validate our observations in another PAAD cohort, though indirect validation results of HLA-A02+B62+B44− in public datasets of PAAD are in line with expectations. Besides, examination of tumor immune microenvironment by RNA sequencing was performed in just 44 patients with high-quality tissue specimens and protein data of tumor-infiltrating lymphocytes of this cohort is absent. Multiplex immunohistochemistry may further reveal and verify the associations of specific HLA-I genotypes with tumor immune microenvironment.While we provide considerable evidence supporting the prognostic value of specific +B62+B44−, was a potential predictor for DFS in PAAD patients after surgery, especially in stage I–II or low CA 19-9 (≤37 U/ml) patients. Mechanistically, patients with HLA-A02+B62+B44− was associated with high rate of KRAS G12D and TP53 mutations, lower HLA-A expression, and less inflamed T-cell infiltration. Together, a comprehensive assessment of the battle between driving tumor cells versus personalized immune system other than focusing on one side of the matter can better appreciate interindividual survival differences in resected PAAD.In summary, the current study suggested that specific combination of germline HLA-A02/B62/B44 supertype, HLA-A02This study was approved by the Medical Ethical Committee of the Hospital and performed in accordance with relevant guidelines . All patients signed an informed consent form before this study.This work was supported by grant from the National Natural Science Foundation of China  and the Shanghai Sailing Program (No. 20YF1426900). Besides, this study was granted by the National Key Sci-Tech Special Project of China (No. 2018ZX10302207).L.Z., Q.Z., and C.W.: conception and design. B.S., Ha.C., H.Z., and L.L.: project supervision. Y.Y., D.R., L.Z., H.S., Hu.C., and B.M.:bioinformatic and statistical analysis. L.Z., Q.Z., C.W., and Y.Y.: data mining and interpretation. Y.Y., D.R., and L.Z.: figures. Y.J., Z.Z., S.Z., F.L., J.J., X.L., J.X., D.C., and Z.X.: selection and collection of clinical samples and clinical data. J.Z., J.W., X.D., C.P., H.L., C.J., Hu.C., and B.M.: constructive advising and discussion. L.Z., Y.Y., Q.Z., C.W., B.S., Ha.C., H.Z., and L.L.: manuscript writing and editing. All authors have read and approved the final manuscript.The authors declare that they have no financial conflict of interest with regard to the content of this report.Name of the registry: Clinicaltrials.govUnique Identifying number or registration ID: NCT05483257https://www.clinicaltrials.gov/ct2/show/NCT05483257?term=NCT05483257&draw=2&rank=1Hyperlink to your specific registration (must be publicly accessible and will be checked): Baiyong Shen and Henghui Zhang.http://cbioportal.org/msk-impact; ICGC-PAAD, https://dcc.icgc.org/projects/PACA-CA; Metastatic PAAD cohort, cBioPortal for Cancer Genomics at: http://cbioportal.org/msk-impact; ICB cohort, DOI: 10.1126/science.aao4572. The raw sequence data reported in this paper have been deposited in the Genome Sequence Archive in National Genomics Data Center under accession number HRA000456 that are publicly accessible at: http://bigd.big.ac.cn/gsa-human. All other data are available from the corresponding authors upon reasonable request.The public datasets from prior studies are available at the following accession numbers: TCGA-PAAD, cBioPortal for Cancer Genomics at: Not commissioned, externally peer-reviewed.


Substitution of Ala1016 with bulkier hydrophobic residues in the context of a prefusion-stabilized S trimer, S2P-FHA, was associated with increased thermal stability. S glycoprotein membrane fusion function was retained with Ala1016/Ala1020 cavity-filling mutations associated with improved recombinant S2P-FHA thermostability, however 2 mutants, A1016L and A1016V/A1020I, lacked ability to mediate entry of S-HIV-1 pseudoparticles into 293-ACE2 cells. When assessed as immunogens, two thermostable S2P-FHA mutants derived from the ancestral isolate, A1016L (16L) and A1016V/A1020I (VI) elicited neutralizing antibody with 50%-inhibitory dilutions (ID50s) in the range 2,700–5,110 for ancestral and Delta-derived viruses, and 210–1,744 for Omicron BA.1. The antigens elicited antibody specificities directed to the receptor-binding domain (RBD), N-terminal domain (NTD), fusion peptide and stem region of S2. The VI mutation enabled the production of intrinsically stable Omicron BA.1 and Omicron BA.4/5 S2P-FHA-like ectodomain oligomers in the absence of an external trimerization motif (T4 foldon), thus representing an alternative approach for stabilizing oligomeric S glycoprotein vaccines.The spike (S) glycoprotein of SARS CoV-2 is the target of neutralizing antibodies (NAbs) that are crucial for vaccine effectiveness. The S1 subunit binds ACE2 while the S2 subunit mediates virus-cell membrane fusion. S2 is a class I fusion glycoprotein subunit and contains a central coiled coil that acts as a scaffold for the conformational changes associated with fusion function. The coiled coil of S2 is unusual in that the 3–4 repeat of inward-facing positions are mostly occupied by polar residues that mediate few inter-helical contacts in the prefusion trimer. We examined how insertion of bulkier hydrophobic residues  to fill a cavity next to Ala First-generation SARS CoV-2 vaccines that generate immune responses to ancestral Spike glycoprotein sequences have averted at least 14.4 million deaths, but their effectiveness against the recently emerged Omicron lineages is reduced. The updating of booster vaccines with variant Spike sequences are therefore likely required to maintain population immunity as the pandemic continues to evolve. The Spike is a trimeric integral membrane protein with a membrane spanning sequence at its C-terminus. The Spike protein-based vaccine that is currently licensed for human use is produced by a complex process that reconstitutes the Spike in an adjuvanted nanoparticle. Alternatively, production of the Spike trimer as a soluble protein generally requires replacement of the membrane spanning sequence with a foreign often highly immunogenic trimerization motif that can complicate clinical advancement. We used systematic structure-directed mutagenesis coupled with functional studies to identify an alternative stabilization approach that negates the requirement for an external trimerization motif or membrane-spanning sequence. The replacement of 2 alanine residues that are associated with a cavity in the core of the Spike trimer with bulkier hydrophobic residues resulted in increased Spike thermal stability. Thermostable Spike mutants retained major conserved neutralizing antibody epitopes and the ability to elicit broad neutralizing antibody responses. One such mutation, referred to as VI, enabled the production of intrinsically stable Omicron variant Spike ectodomain oligomers in the absence of an external trimerization motif. The VI mutation potentially enables a simplified method for producing a stable oligomeric S ectodomain glycoprotein vaccine. A membrane-spanning sequence at the C-terminus of S2 stabilizes the trimer and anchors it to the viral or cell membrane  as a function of temperature is shown.(JPG)Click here for additional data file.S2 FigA.Gaussia luciferase activity produced by effector cells used in the luciferase reporter assay of cell-cell fusion shown in B. Approach used to obtain magnified fields shown in Fig 2D from the whole field image (left panel). Corresponding bright field, Hoechst 33342 and EGFP images are stacked at right. C, Bright field, Hoechst 33342, EGFP, merged images and enlargements of the merged images (left to right) corresponding to those shown in Fig 2D.(PPTX)Click here for additional data file.S3 FigA, Infectivity of S-HIV-1 luciferase reporter pseudoviruses. S-HIV-1 pseudoviruses were produced by transfected 293T cells for 72 h after which transfection supernatants were filtered, diluted 1/10 and used to inoculate 293-ACE2 cells expressing TMPRSS2. The cells were lysed and assayed for firefly luciferase activity 72 h days later. The means ± SEM shown (n = 8). ns, not significant, ***, P < 0.001, ****, P < 0.0001 versus WT, Kruskal-Wallis test. B, p24/CA content of pelleted pseudoviruses from transfections in A. The p24/CA band was revealed by SDS-PAGE and western blotting with anti-CA antibody 183- and AlexaFluor688-labeled goat-anti-mouse immunoglobulin. C, S content of S-HIV pseudoviruses pelleted by ultracentrifugation through a sucrose cushion. The S band was revealed by SDS-PAGE and western blotting with polyclonal anti-S1 antibody and goat anti-rabbit immunoglobulin IRDye800CW. m, molecular weight markers.(JPG)Click here for additional data file.S4 FigA, Reactivity of immune sera with S fragments in ELISA. Immune sera were titrated on S2P-FHA and subdomains thereof derived from the Hu-1 ancestral strain. Binding titers were defined as the reciprocal dilution of serum giving an optical density ten-times that of background, as defined by binding to BSA. B. Reactivity of mNAbs and S-derived glycoproteins and subdomains used in panels A and C in ELISA. C, Epitope specificity of immune sera assessed by competition ELISA. Competition ID50s of vaccinal sera versus ACE2-Fc or mNAbs for binding to streptavidin-captured ancestral Hu-1 biotin-S2P-FHA. Serially diluted vaccinal sera were mixed with constant amounts of ACE2-Fc and human monoclonal anti-S IgGs prior to incubation with streptavidin captured biotin-S2P-FHA. The immunogen groups are indicated below the graphs. A Kruskal-Wallis test was used to determine that the differences in ID50s observed between groups was not significant (ns). The horizontal dotted lines indicates that the ID50s of control sera were >1/20. D, Binding of immune sera to biotin-S2P-FHA captured on streptavidin-coated plates in ELISA.(JPG)Click here for additional data file.S5 FigBinding of S2P-derived analytes to S ligands immobilized on anti-human IgG capture biosensors. Association was for 300 sec followed by dissociation for 300 sec. The binding kinetics are shown in (JPG)Click here for additional data file.S6 FigA, Superose 6 SEC of S2P.OmiBA4/5.VI-1208 and SnoP.OmiBA4/5.VI-1208 trimers. B, SYPRO orange thermofluor assay of S2P.OmiBA4/5.VI-1208 and SnoP.OmiBA4/5.VI-1208 trimers.Reversion of the 2P mutation to Lys986-Val987 in SnoP.OmiBA4/5.VI-1208 reduces trimer yield but maintains thermostability. (JPG)Click here for additional data file.S7 FigRepresentative raw EM micrographs of negatively-stained S2P.OmiBA1-FHA (left), S2P.OmiBA1.VI-1208 (middle) and S2P.OmiBA4/5.VI-1208 (right) and corresponding representative 2D class averages. The class averages, derived from ~10,000 particles per sample, revealed the S2P.VI protein samples to be predominantly in forms consistent with the pre-fusion trimer (classes shown ranked by abundance). A small percentage of the rod-shaped putative post-fusion form (highlighted within red boxes) was observed in the S2P.OmiBA1-FHA (8.0%) and S2P.OmiBA1.VI-1208 (8.8%) samples.(JPG)Click here for additional data file.S1 Table(PDF)Click here for additional data file.


Breast cancer represents the second most deadly malignancy in women, and long noncoding RNAs (lncRNAs) have crucial functions in its development.CDKN1A antisense DNA damage-activated RNA (PANDAR) on epithelial-mesenchymal transition (EMT) in breast cancer cells and their proliferation.To investigate effects of the promoter of PANDAR was overexpressed in Michigan cancer foundation 7 (MCF-7) breast cancer cells. E-cad and N-cadherin  levels were detected by immunoblotting. Cell viability was assessed using a cell counting kit-8.lncRNAs potentially regulating the transcriptional activity of the E-cadherin  gene promoter were screened using a dual-luciferase reporter assay. PANDAR and TCONS00068220/LOC105375819 conservatively regulated the promoter activity of E-cad. PANDAR overexpression in MCF-7 inhibited E-cad expression, but upregulated N-cad. The enhanced expression of PANDAR promoted cell proliferation.PANDAR is a key transcriptional repressor of E-cad and has regulatory effects on the promotion of cell proliferation. PANDAR is an oncogene in breast cancer, potentially facilitating the EMT process and promoting cell proliferation. Breast cancer is a major malignancy affecting women worldwide . AnnuallEpithelial-mesenchymal transition (EMT) is a process by which epithelial cells undergo transformation to acquire mesenchymal features, generating malignant cells harboring stem cell-like properties, also known as cancer stem cells (CSCs), including migration and invasion, reduced apoptosis and senescence, and drug resistance , thus faH19 promotes breast cancer cell proliferation, clone formation, and metastasis, and further generates CSCs [CDKN1A anti-sense DNA damage-activated RNA  is a noncoding RNA located on chromosome 6p21.2, whose abnormal expression is involved in the pathogeneses of various cancers [INK4A expression, PANDAR modulates G1/S arrest in breast cancer cells [PANDAR levels in colon cancer predict poor patient prognosis and promote metastasis through EMT [Long noncoding RNAs (lncRNAs) constitute a group of small RNAs with >200 bp and without an open reading frame, which inhibit the expression of downstream genes predominantly by affecting the activity of the upstream promoter region . lncRNAstes CSCs . Howeverough EMT . lncRNAsough EMT , 17, 18.PANDAR on EMT and proliferation in breast cancer cells.Here, we assessed the effects of 2 in air at 37 °C. Cell identity had been confirmed by short tandem repeat DNA profiling, and PCR had been used to confirm the absence of any mycoplasma contamination.Human breast invasive ductal carcinoma Michigan cancer foundation 7 (MCF-7) cells were obtained from the American Type Culture Collection , HEK-293T cells  were obtained from the China Center for Type Culture Collection of the National Collection of Authenticated Cell Cultures Cell Bank affiliated with the Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, and these were maintained in Dulbecco's modified Eagle's medium  containing 10% fetal bovine serum (Gibco), penicillin (100 U/mL), and streptomycin (100 mg/mL). Cells were incubated in culture medium under a humidified atmosphere of 5% COTCONS00068220 (XR_928848.2), which is the same gene as LOC105375819, for HOX transcript antisense RNA , ciR-has_circ_0001073, BX647792, and PANDAR (NR_109836.1), were amplified from human genomic DNA isolated from MCF-7 cells. lncRNA were then cloned into the pLVX-Puro vector to construct a series of lncRNA plasmids. Circular RNA ciR-has_circ_0001073 was cloned into pLCDH-ciR vector. Primer sequences are listed as follows: HOTAIR forward (F): CAAGCTTCGAATTACGAATTCGACTCGCCTGTGCTCTGGAGCTTG; HOTAIR reverse (R): TTATCTAGAGTCGCGGGATCGGAAAATGCATCCAGATATTAATAT; BX647792 F: CAAGCTTCGAATTACGAATTCGGCCAGAAGGGGAGGAAATTGGAA; BX647792 R: TTATCTAGAGTCGCGGGATCGCCAGTTTTTCCAACTTCCCCTTTC; LOC105375819 F: CAAGCTTCGAATTACGAATTCCCGACTTTCACTTATCAGACCTTG; LOC105375819 R: TTATCTAGAGTCGCGGGATCGGGTGAGCAGTTTTTATTAACCTGT; PANDAR F: CAAGCTTCGAATTACGAATTCTTTCAGGAATGCCGCAGATGTACA; PANDAR R TTATCTAGAGTCGCGGGATCGCAGTGGCTCACGCCTGTAATCTCA; ciR-hsa_circ_0001073 F: ACCTCCATAGAAGATTCTAGAGAGTTCTAAAATTAAACTATGTGG; ciR-hsa_ circ_0001073 R: CTCAGCGCCACAGCAGAATTCGTTAATTGAACAGATTTTATTTTA.The genes of lncRNAs, including Renilla luciferase activity was calculated and results were normalized to the corresponding negative control. Data are represented as the mean ± standard deviation (SD) of triplicate assays. Significant differences from controls are indicated by *P < 0.05, **P < 0.01.The human and mouse E-cad gene promoters (Nos. 42081 and 61798) reporter plasmids were purchased from Addgene. lncRNA expression vectors, reporter plasmid containing mouse E-cad promoter, and internal control plasmid pRL-TK were cotransfected into HEK-293T cells. The pRL-TK vector served as a reference for normalizing transfection efficiency. At 48 h after transfection, dual-luciferase assays were performed by using a dual-luciferase reporter assay kit (Promega), according to the manufacturer's instructions. The ratio of firefly-to-6 cells/dish. On the next day, a mixture of 5 μg pLVX-PANDAR or pLVX-Puro, 3.75 μg psPAX2 , and 1.25 μg pMD2.G  were diluted into 1 mL opti-MEM medium (Invitrogen); then, 30 μL PEI solution  was added and mixed thoroughly. The mixture was incubated at room temperature for 25 min to prepare the transfection complexes. Then, the mixture was added dropwise into the abovementioned LentiX-293 cells. At 48 h after transfection, the supernatants were collected and centrifuged at 40,000 × g to collect lentivirus pellets. We used 1 mL DMEM medium to resuspend the lentivirus. MCF-7 cells (1 × 106 cells in a 60 mm dish) were infected with each lentivirus at a multiplicity of infection (MOI) of 1. At 48 h after infection, stable cell lines were selected by adding 1 μg/mL puromycin (Sigma).LentiX-293 cells were seeded into a 10 cm dish at 2.5 × 10GAPDH QRT F: CCCATGTTCGTCATGGGTGT; GAPDH QRT R: TGGTCATGAGTCCTTCCACGATA; PANDAR F: TCAGGAATGCCGCAGATGTA; PANDAR R: GACCGTGTCTGGAGGATGCC.Total RNA was extracted from cells using TRIzol reagent (Invitrogen) according to the manufacturer's instructions. The cDNA was synthesized through reverse-transcription reaction with Rever-Tra-Ace-α-Transcriptase (Toyobo) and subsequently amplified by PCR using SYBR Premix Ex Taq II (Tli RNaseH Plus) (TaKaRa Bio). The primer sequences used in quantitative real-time polymerase chain reaction (qRT-PCR) are listed as follows: g . Subsequently, proteins were separated by 10% SDS-polyacrylamide gel electrophoresis (SDS-PAGE) and electro-transferred onto polyvinylidene difluoride (PVDF) membranes . After blocking nonspecific binding sites with 5% nonfat milk for 1 h at ambient room temperature, they were incubated overnight at 4 °C with mouse monoclonal primary antibodies against E-cad , N-cad , and β-actin  (Santa Cruz Biotechnology). Then, horseradish peroxidase (HRP)-linked goat secondary anti-mouse antibodies  were added at ambient room temperature and incubated with the proteins transferred to the membrane for 1 h. Immunoreactive signal was developed and visualized with enhanced chemiluminescence (ECL) reagents (Millipore).The harvested cells were pelleted and resuspended in sodium dodecyl sulfate (SDS) lysis buffer  and incubated on ice. The lysates were centrifuged at 8,000 × PANDAR or control cells were seeded into 96-well plates at 2 × 103 cells/well. Then, 10 μL CCK-8 reagents  were added per well for the indicated time, followed by further incubation at 37 °C for 2–4 h. Optical density was measured at 450 nm on a microplate reader (Bio-Rad).A cell counting kit-8 (CCK-8) was used to assess cell viability. Briefly, MCF-7 stable cell line overexpressing t test (two-tailed) was performed to compare parametric data. Differences with P < 0.05 were considered significant.Data are shown as means ± SD calculated by WPS Office 2019. The empirical data obtained from all experiments were fitted to histograms using GraphPad Prism 7 software. The experiments were performed in triplicate and repeated (more than once). A Student Figure 1A–E). Then, we screened noncoding RNAs that potentially regulated the E-cad gene promoter by dual-luciferase reporter assay, including HOTAIR, LOC105375819, BX647792, and PANDAR. The human E-cad promoter reporter plasmid and a series of lncRNAs or circular RNAs were cotransfected into HEK-293T cells. We found that the overexpression of ciR-hsa_circ_0001073 (1.148 ± 0.014) and LOC105375819 (1.205 ± 0.019) significantly increased the luciferase activity, whereas overexpression of PANDAR (0.897 ± 0.041) suppresses the luciferase activity . This finding suggests that ciR-hsa_circ_0001073, LOC105375819, and PANDAR may regulate E-cad expression in human cells.E-cad, a biomarker of epithelial cells, is downregulated in the EMT process. Therefore, lncRNAs altering E-cad expression are involved in carcinogenesis. We constructed a series of noncoding RNA expression vectors and verified their overexpression effects in HEK-293T cells  remarkably increased luciferase activity, which was reduced by PANDAR (0.692 ± 0.071) and BX647792 (0.566 ± 0.032) . These findings indicated that LOC105375819 and PANDAR regulated the promoter activity of the E-cad gene with evolutionary conservatism.To explore which regulation mechanism is evolutionarily conservative, the mouse E-cad promoter reporter vector and a series of lncRNAs or circular RNAs were cotransfected into HEK-293T cells, respectively. This was done to assess whether the abilities of PANDAR modulated E-cad promoter activity, we hypothesized that it might contribute to modulating the EMT process. First, PANDAR was overexpressed in MCF-7 cells by using lentivirus, and then qRT-PCR was used to detect the efficiency of overexpression of PANDAR . Further, western blotting was performed to determine the expression profile of EMT-related proteins, including E-cad, and N-cad protein. As depicted in Figure 2B, an increased PANDAR expression led to elevated N-cad levels. However, it reduced E-cad levels compared with the control group, suggesting that it may potentially control EMT in breast cancer.Because PANDAR or corresponding control was seeded into 96-well plates with the same density, followed by the photomicrographs and CCK8 assay to quantitate cell proliferation at indicated times . The overexpression of PANDAR significantly increased MCF-7 cell proliferation at day 3 post-plating (1.000 ± 0.120 vs 1.412 ± 0.105). This significant increase in MCF-7 cell proliferation suggests that PANDAR is an oncogene regulating breast cancer proliferation.MCF-7 cell expressing PANDAR, LOC105375819, HOTAIR, ciR-has_circ_0001073, BX647792, and PANDAR were compared with the control group. The results revealed that LOC105375819 significantly promoted the transcription of the E-cad promoter, whereas PANDAR significantly inhibited the transcription of the E-cad promoter. Indeed, it was previously reported that high expression of PANDAR in colon cancer predicts poor patient prognosis and promotes metastasis through EMT [PANDAR regulating E-cad remains unclear. The weak regulatory effect of PANDAR on E-cad promoters may imply an indirect regulation.Several previously constructed recombinant lncRNA plasmids were screened by dual-luciferase reporter assay. In the present research, ough EMT . The regPANDAR inhibited the expression of the E-cad. The core promoter region of the E-cad gene derived from humans differs considerably from that found in mice. However, the human gene for PANDAR also regulated the E-cad promoter of mice, which further implies that the regulatory effect of PANDAR on the E-cad promoter may depend on a small number of nucleic acids or a spatial structure of the promoter that is evolutionarily conserved.Western blotting was performed to determine the expression profile of EMT-related proteins, including E-cad, and N-cad. The results show that PANDAR was overexpressed in MCF-7 cells through lentiviral infection, followed by the CCK8 assay to quantify cell proliferation. The CCK-8 assay also established that PANDAR upregulation markedly enhanced proliferation of MCF-7 cells. A previous study revealed that PANDAR is activated in a p53-dependent fashion and interacts with nuclear transcription factor YA (NF-YA) to suppress proapoptotic genes, thereby inhibiting cell apoptosis [PANDAR plays an oncogenic role in bladder cancer by inducing cell proliferation and suppressing proapoptotic pathways [PANDAR was demonstrated to modulate G1/S arrest in breast cancer cells via p16INK4A downregulation [PANDAR promotes breast cancer cell proliferation.By contrast, poptosis . Additiopathways . PANDAR gulation . These dPANDAR regulates the inhibition of the promoter activity of the E-cad gene and promotes breast cancer cell proliferation. Although further functional experiments are necessary, the current findings provide new insights into the molecular mechanisms underpinning PANDAR's effect on the EMT process in breast cancer.The lncRNA