LncRNA PCSK1N-202 regulates CD34 + hematopoietic cells proliferation in MDS patients via PIM2/HIF-1alpha

LncRNA PCSK1N-202 regulates CD34 + hematopoietic cells proliferation in MDS patients via PIM2/HIF-1alpha | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article LncRNA PCSK1N-202 regulates CD34 + hematopoietic cells proliferation in MDS patients via PIM2/HIF-1alpha Zhaoyun Liu, Mengyue Tian, Yue Jia, Yixuan Guo, Xianghong Zhao, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3177358/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Myelodysplastic syndromes (MDS) are characterized by malignant clonal hematopoietic stem cells with high-risk of progression to acute myeloid leukemia (AML). Results In this study,we explore the role of PIM2/HIF-1alpha in the proliferation of CD34 + cells in MDS patients. We investigate the profile of lncRNA derived from the bone marrow CD34 + cells in MDS patients and AML secondary to MDS (sAML) patients. We found 1173 lncRNAs (648 upregulated/525 downregulated) and 326 mRNAs (125 upregulated/201 downregulated) significantly deregulated in sAML compared to those in MDS patients (|logFC| > 1, p value < 0.05). Of these, lncRNA PCSK1N-202 predicted as targeted-regulator to PIM2.RT-PCR showed that the level of PCSK1N-202 was upregulated in AML and MDS patients and positive related with PIM2.For further demonstrated the regulation of PCSK1N-202 to PIM2,RNA fluorescence in situ hybridization indicated that PCSK1N-202 was distributed in the nucleus and cytoplasm which as well as PIM2.For functional study, SKM-1 cell was transfected with LV- PCSK1N-202 ,which induced the decline of PIM2 and HIF-1α followed with decreased of cell proliferation and increased of apoptosis. Conclusion In conclusion, the upregulation of PCSK1N-202 transcript may through PIM2 / HIF-1α regulate the proliferation of CD34 + cells in MDS. Myelodysplastic syndromes CD34+ cell PIM2 LncRNA lncRNA-seq PIM2/HIF-1α Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Myelodysplastic syndrome (MDS) is a group of malignant clonal hematopoietic stem cell diseases characterized by ineffective hematopoiesis and pathological hematopoiesis resulting in a f and a high risk of transformation to acute myeloid leukemia (AML)[ 1 ]. The use of new drugs of azacytidine, decitabine and lenalidomide has indeed played a role in delaying disease progression and improving clinical symptoms in some MDS patients, but it is still unable to completely improve the prognosis of patients. In particular, the conversion to acute myeloid leukemia in high-risk MDS patients remains an urgent problem. Therefore, exploring the molecular mechanisms related to the malignant proliferation of MDS hematopoietic stem cells may provide new therapeutic tools for MDS patients, prolonging their trans-AML cycle and survival cycle and improving their quality of life. For high-risk MDS patients and trans-AML patients, malignant proliferation of bone marrow hematopoietic stem cells is the most prominent feature. With the development and application of second-generation sequencing technology, more and more studies have confirmed that malignant clones of MDS are caused by multiple genetic mutations occurring sequentially. These mutations are involved in various cellular functions such as RNA splicing, chromatin modification, epigenetic regulation, DNA damage and stress response [ 2 – 5 ] . PIM(The proviral insertion site in Moloney murine leukemia virus) is a family of serine/threonine kinases with three members, PIM1, PIM2, and PIM3. PIM2 is highly homologous to PIM1 and PIM3, which have similar oncogenic functions [ 6 ]. Two PIM2 subtypes ( 34,40 kDa ) were detected in human cells, but 34 - kDa PIM2 subtype mainly played a role in tumor progression. PIM2 is highly expressed in many malignant tumors, such as breast cancer, lung cancer, liver cancer, brain cancer, renal cancer, prostate cancer, leukemia and multiple myeloma[ 7 ]. As a serine / threonine kinase, PIM2 functions through phosphorylation of several substrates, including c-MYC, Notch1, Rela, p21, p27, BAD, PKM2, HK2 and TSC2[ 8 ]. PIM kinase promotes cancer cell growth and migration by regulating cell cycle, apoptosis and proliferation. In acute leukemia, PIM2 inhibitors promote apoptosis and inhibit cancer cell proliferation in leukemic cells by decreasing the expression of c-Myc-(Ser62), 4E-BP1 (Thr36/Thr47) and the apoptotic proteins Bcl-2, Bcl-xL, XIAP[ 9 ]. It has been shown that PIM2 and HIF-1α promote and induce each other in a hypoxic environment[ 10 ], leading to malignant proliferation of hepatocellular carcinoma cells. PIM2 enhances the stability of HSF1 protein by phosphorylating HSF1 Thr120 to induce PD-L1 expression and promotes the proliferation of breast cancer cells in cell and xenograft mouse models. The overexpression of PIM2 up-regulates HIF1α and VEGF, enhances angiogenesis, and causes the progression of hepatocellular carcinoma. In addition, the up-regulation of PIM2 can increase the expression of MMP9 and enhance the metastasis ability of hepatocellular carcinoma cells, which is crucial for the development of advanced hepatocellular carcinoma[ 11 ]. An increasing number of studies have shown that PIM kinases play a crucial role in a variety of tumors, and therefore PIM inhibitors have become a hot research topic as therapeutic targets [ 12 ]. So far, PIM inhibitors have been used in clinical trials for the treatment of leukemia or multiple myeloma [ 13 ]. PIM inhibitors have been shown to significantly inhibit the proliferation of B-ALL cell lines by blocking the cell cycle in the G0/G1 phase, and to induce apoptosis by mediating the JAK2/STAT3 pathway via HO-1. A clinical trial of PIM inhibitors in patients with multiple myeloma showed that PIM447, a novel pan-PIM inhibitor, showed strong synergistic effects with different standard treatment regimens such as bortezomib + dexamethasone, lenalidomide + dexamethasone and pomalidomide + dexamethasone[ 14 ]. Thus PIM2 inhibitors may become an important therapeutic strategy for targeting MM cell-bone marrow interactions[ 15 ]. Only 2% of RNA in the human genome is involved in protein transcription and translation, while the remaining 98% does not have protein-coding functions and is therefore collectively referred to as non-coding RNA. LncRNA (long non-coding RNA) is an RNA that does not encode proteins and > 200 nucleotides in length[ 16 ]. The human genome has over 15,000 lncRNAs that play a role in many life activities and can function in a variety of ways. LncRNAs can recruit different components of the chromatin remodeling complex to alter chromatin organization[ 17 , 18 ]. LncRNAs can affect cellular function through a range of mechanisms, and it is not surprising that these molecules are utilized in different types of cancers. They have been shown to regulate cancer cell proliferation, migration, immune escape and apoptosis, as well as other common features of cancer progression[ 16 , 19 ]. LncRNA analysis by NLCFA technique in 10 cases of MDS (RAEB-2) versus 6 normal controls revealed that the expression levels of up to 51 long-chain non-coding RNAs were different [ 20 ]. In addition, four LncRNAs (TC07000551.hg.1,TC08000489.hg.1, TC02004770.hg.1, and TC03000701.hg.1) were found to be associated with overall survival and risk stratification in MDS patients by LncRNA assays in 176 MDS patients, and detection of these LncRNAs in patients suggesting poor prognosis[ 21 ]. In addition, overexpression of LncRNA CCAT2 in mice promoted tumorigenesis in MDS mice, and increased levels of CCAT2 expression were found in MDS patients [ 22 ]. Neal S. Young[ 23 ] also found 2892 LncRNAs in MDS by single-cell gene sequencing, of which 2084 were unknown LncRNAs, and further found that LncRNAs play an important role in hematopoietic stem cell differentiation. It is suggested that LncRNAs play an important role in the development of MDS. Here,we find PIM2 expression levels correlate with overall survival in myeloid malignancies,and the LncRNA PCSK1N-202 may through PIM2 / HIF-1α regulate the proliferation of CD34 + cells in MDS. Materials and methods Patients The study was obtained from 54 patients who visited the Department of Hematology, General Hospital of Tianjin Medical University from July 2017 to April 2018 by primary diagnosis, including 36 patients with MDS,18 patients with AML,23 healthy donors(HD). MDS patients all met the diagnostic criteria established by WHO 2016 and were typed according to WHO 2016. The basic information of the study subjects is detailed in Table 1 . Table 1 Patients and clinical characteristics Number of samples Age Sex male female MDS patients 36 59.4(30–84) 19 17 2016 WHO type SLD MLD RS EB-1 EB-2 1 49 1 0 5 63.6(59–67) 4 1 6 67.5(56–84) 4 2 7 51.9(30–66) 2 5 17 59.1(44–75) 8 9 AML patients 18 51.9(20–78) 10 8 HD 23 47.7(23–79) 6 17 Note: SLD, MDS with single lineage dysplasia; MLD, MDS with multilineage dysplasia; RS, MDS with ringed sideroblast; EB, MDS with excess blasts;AML, Acute myeloid leukemia. CD34 + cells sorting Bone marrow was obtained from MDS patients, AML patients and healthy donors. Bone marrow mononuclear cells were isolated using density gradient centrifugation(Solarbio, Beijing), CD34 + cells were isolated in MACS(Miltenyi Biotec, Germany) using the CD34 + Cell Isolation Kit(Miltenyi Biotec, Germany) according to the instructions, and CD34 + cell purity was determined to be > 95% by flow cytometry. Biological information analysis of CD34 + cells by lncRNA sequencing: The above obtained CD34 + cells were placed in Trizol(Thermo Fisher Scientific, America) to obtain total RNA. Total RNA was sequenced and bioinformatically analyzed (Shanghai GeneMed Technology Co., Ltd.). The experimental procedure includes: Total RNA sample detection, rRNA removal, double-stranded cDNA synthesis, end repair, addition of sequencing junction, fragment selection, degradation of cDNA second strand, PCR enrichment, library quality control, and sequencing on the machine. The sequencing platform was novaseq 6000.The raw reads per sample has been listed in table S1. GO and KEGG enrichment analysis of target genes of differentially expressed lncRNAs was implemented by the cluster Profiler R package, in which gene length bias was corrected. Clinical outcome analysis The TCGA dataset ( https://portal.gdc.cancer.gov/repository ) was used to get RNA-sequencing expression profiles and clinical information for AML[ 24 ]. The maximum number of clusters is 6, and 80 percent of the whole sample is drawn 100 times, using the ConsensusClusterPlus R package (v1.54.0)[ 25 ], clusterAlg = "hc," inner Linkage='ward. D2'. For clustering heatmaps, use the R software package pheatmap (v1.0.12, https://cran.r-project.org/web/packages/pheatmap/index.html ). The current-release (V8) GTEx datasets were obtained from the GTEx data portal website ( https://www.gtexportal.org/home/datasets ). The Kaplan-Meier survival analysis was performed by the R program ggplot2. All the analysis methods and R package were implemented by R software (version 4.0.3). P-value < 0.05 was considered statistically significant. Real-Time Polymerase Chain Reaction Analysis (RT-PCR): CD34 + T cells were added to trizol to extract total RNA, and reverse transcribed cDNA was prepared according to the instructions of the Tiangen Reverse Transcription Kit(Tiangen, Beijing), and placed in an IQ5 real-time fluorescence quantitative PCR instrument using the SuperReal PreMix Plus (SYBR Green) system, and GAPDH was used as an internal reference to assess the relative expression of each target gene according to 2 −ΔΔCT method. The sequences of cDNA primers (Biotech Bioengineering Co., Ltd.) designed for the target genes PIM2, HIF-1α, IDH1 and internal reference genes are shown in Table 2 . Table 2 qRT-PCR primer sequences Gene Primer sequences (5′-3′) HIF-1α Forward-ACG TTC CTT CGA TCA GTT GTC ACC Reverse-GGC AGT GGT AGT GGT GGC ATT AG IDH-1 Forward-TCA GTG GCG GTT CTG TGG TAG AG Reverse-CAT CCT TGG TGA CTT GGT CGT TGG PIM2 Forward-TTG GGA AGG AAT GGT AGA TG Reverse-CAG GAG AAC AAA CAG CAA GC GAPDH Forward-GGA GCG AGA TCC CTC CAA AAT Reverse-GGC TGT TGT CAT ACT TCT CAT GG Cell culture : The cell line SKM1 used in this experiment was purchased from the National Biomedical Experimental Cell Library, and the whole culture process was completed in the sterile ultra-clean platform. The medium for SKM-1 was RPMI 1640(Solarbio, Beijing) containing 15% fetal bovine serum(Gibco, America). Planted at a density of 1х10 6 /ml in T25 flask(Corning, America) and cultured in 37°, 5%CO 2 incubator. When the cell density reached about 90%, the cell suspension was sucked into 15 ml sterile centrifuge tube, 800–1000 rpm, centrifuged for 5 minutes. Discard the supernatant and add 2 times fresh medium into two culture flasks. And use this passaged cell line for subsequent experiments. SiRNA knock-down : The number of cells in each well was controlled to be 4 ~ 8х10 5 in the 24-well plate, and the PIM2 targeted siRNA(GenePharma, Shanghai) was transfected with Lipofectamine 2000(Invitrogen, America). siRNA was diluted with 50 µL opti-MEM(Solarbio, Beijing), and 1 µL lipofectamine 2000 was added to 50 µL opti-MEM for dilution to prepare the transfection complex. Add the transfected complexes to the cultured cells and shake them gently. Cultured in 37℃, 5% CO 2 incubator for 48 hours and harvested for subsequent experiments. Lentiviral transfection: A total of 8mL SKM-1 cell suspension with a density of 1х10 5 /mL was prepared using a complete medium, and the experiment was divided into four groups. 2mL of each well was added into a six-well plate, and four lentiviruses LV-PCSK1N-202-72/73/74 and con313 were added respectively ( Shanghai Jikai Gene Medical Technology Co., Ltd.). The cells were cultured in a 37°, 5% CO 2 cell incubator for 24 hours. The cells in each well were collected into the EP tube and centrifuged at 200 хg for 2 min. The supernatant was removed and replaced with a fresh medium. After gently blowing and mixing, the cells were put back into the incubator. The transfection efficiency was observed by fluorescence microscope and flow cytometry 72 hours after infection. Appropriate amount of cells were collected for subsequent experiments. Western Blot Proteins were extracted with lysis buffer. after SDS-PAGE, the samples were transferred to PVDF membranes(Easybio, Beijing). Next, the membranes were closed with 5% skim milk, and after membrane incubation with dilute antibody at 1:1000 concentration(CST, America), the membranes were rinsed with TBST(Solarbio, Beijing) and HRP-coupled di-incubated with dilute antibody༈CST, America༉ at 1:5000 concentration for 1 hour. After rinsing with TBST, a luminescent solution was prepared by thoroughly mixing liquid A and liquid B from the ECL chemiluminescence kit(Cell Signaling Technology, America), added to the PVDF membrane, and subsequently exposed in a fluorescence imager. Cell proliferation assay. Configure EdU working solution and add 1 ml of cell suspension in a 6-well plate. Place the six-well plate in a cell incubator and incubate the cells for 2 hr. Collect the cells and fix them for 15 min at room temperature using 1 ml of fixative solution (paraformaldehyde) and wash. Add 1 ml of permeabilization solution (PBS containing 0.3% Triton X-100) (Solarbio, Beijing) to each well and incubate for 15 min at room temperature and wash. Configure Click reaction solution, mix with cell blowing and incubate for 30 min at room temperature protected from light.After washing, fluorescence detection was performed on a Beckman Coulter flow cytometer with APC fluorescence channel. Apoptosis assay. SKM-1 cells were collected by centrifugation at 2000 rpm for 5 min and washed. Dilute 10×Binding Buffer tenfold, add 5µL of 7-AAD dye to 50µL of 1×Binding Buffer, shake and mix, and incubate for 15min at room temperature, protected from light. 450µL of 1×Binding Buffer was added and mixed, 5µL of Annexin V-PE(BD, America) is added and mixed, and incubated for 15min at room temperature, protected from light. The cells were detected by Beckman Coulter flow cytometer within 1 h. Annexin V was detected by the orange-red fluorescence channel of PE, and 7-AAD red fluorescence was detected by the PERCP channel. LncRNA fluorescence in situ hybridization. The probe sequence was designed according to the lncRNA base sequence (Shanghai Gema Pharmaceutical Technology Co., Ltd.), and the reagents were prepared according to the kit instructions. SKM-1 cells fixed in 4% paraformaldehyde were attached to glass slides with a slide machine. The dried cell pictures were placed in a 10cm dish, 100 µl of 0.5% Buffer A was added dropwise, the 0.5% Buffer A was discarded after incubation at room temperature for 15 minutes, and 500 µl of PBS was added dropwise to wash twice, 5 minutes each time. Add 100 µl of blocking solution dropwise to each slide and incubate at 37°C for 30 minutes. Discard the blocking solution, add 100 µl of buffer C dropwise, and incubate for 30 minutes in a 37°C cell incubator. Incubate Buffer E in a 73°C water bath for 30 minutes until the liquid becomes clear. The probe stock solution was diluted 100 times, placed in a 75°C water bath for denaturation for 10 minutes, then mixed with SA-CY3 at a ratio of 8:1, and incubated in a 37°C cell incubator for 30 minutes. Mix the probe working solution mixed in the previous step with 90 µl Buffer E. Place the glass slide horizontally in a wet box, drop the denatured probe mixture prepared in the previous step on the glass slide, cover with a cover glass, and incubate in a 37°C incubator for 12–16 hours. The next day of hybridization, the glass slide was taken out, the cover glass was gently removed, the probe working solution was discarded, 100 µl of 0.1% buffer F was added, and washed at 37°C for 10 minutes. Discard 0.1% buffer F, add 100 µl of 2×Buffer C, wash at 60°C for 10 minutes, and wash 3 times. 100 µl of DAPI working solution was added, and the cells were stained in the dark for 20 minutes. The DAPI working solution was removed and washed twice with PBS for 5 minutes each time. Add anti-quenching agent dropwise, cover with a coverslip, and observe under a fluorescence microscope. Statistical analysis. SPSS software (version.19) and GraphPad Prism (version 7.0) statistical software were used for statistical analysis. Data were numerical variables, and if they conformed to a normal distribution, the three groups were compared with each other by one-way ANOVA; two groups were compared by unpaired t-test, and the data were expressed as mean ± standard deviation. If they did not conform to normal distribution, Kruskal-Wallis test analysis (three groups of data) and Mann Whitney (two groups of data) tests were used, and the median and quartiles were used. Spearman correlation test was used for correlation analysis of the two data sets. Results PIM2 expression levels correlate with overall survival in myeloid malignancies We first analyzed the publicly accessible TCGA database and selected RNA-sequencing datasets of AML as well as clinical data. The RNA-sequencing data (n = 151) were clustered into 6 subgroups based on immunological genes: Cluster 1 (n = 49), Cluster 2 (n = 31), Cluster 3 (n = 15), Cluster 4 (n = 17), Cluster 5 (n = 31), and Cluster 6 (n = 8) (Fig. 1 AB). Then we analyzed the PIM2 expression levels in different clusters and observed that PIM2 expression levels in Cluster 1, 2, and 5 were significantly different (p = 1.3e-06). Specifically, PIM2 expression levels in Cluster 2 were substantially greater than those in Cluster 1 and 5, while there were no significant differences in Cluster 1 and Cluster 5 (Fig. 1 C). Further, we analyzed the prognostic survival of AML patients with Cluster 1, 2, and 5. Cluster 2 patients had a considerably worse overall survival than Cluster 1 and 5 patients (median time: 0.7, 2.2, and 1.8 years, respectively; p = 0.0042) (Fig. 1 D). Taken together, these findings suggest that elevated PIM2 expression may reduce prognostic survival time in a subset of patients with myeloid malignancies. High PIM2 expression levels correlate with lower overall survival in myeloid malignancies. A. consensus clustering cumulative distribution function (CDF) and relative change in the area under the CDF curve (CDF Delta area). The relative change in area under the cumulative distribution function (CDF) curves when cluster number varying from k-1 to k. B. consistency of clustering results heatmap (k = 6), Rows and columns represent samples, the different colors represent different types (Cluster 1 to Cluster 6). C. Cluster 2 had much higher levels of PIM2 expression than Cluster 1 and Cluster 5. D. Kaplan-Meier survival analysis of the Cluster 1, 2, and 5, comparison among different groups was made by log-rank test. 95% CL represents the HR confidence interval; Median time represents the time corresponding to survival in different groups at 50% (median survival time) in years. The median overall survival time of Cluster 2 with high expression of PIM2 was significantly shorter compared to Cluster 1 and Cluster 5. ****p < 0.0001, asterisks (*) stand for significance levels. The statistical difference of two groups was compared through the Wilcox test, significance difference of three groups was tested with Kruskal-Wallis test. lncRNA sequencing and bioinformatic analysis of bone marrow CD34 + cell in MDS patients and sAML patients To investigate the role of lncRNAs in malignant cloning of MDS CD34 + cells and promotion of sAML patients, we performed lncRNA-seq analysis on CD34 + cells from MDS and sAML patients. The screening conditions were: |logFC| > 1, p-value < 0.05. The results identified 1173 lncRNAs (of which 648 were up-regulated and 525 were down-regulated) and 326 mRNAs (of which 125 were up-regulated and 201 were down-regulated) that were significantly altered in sAML compared to the MDS group. The following is the volcano map and clustering heat map of the differential genes obtained from sequencing (Fig. 2 A). In order to study the functions of these differential genes, GO and KEGG enrichment analysis of differential genes was performed. Gene Ontology (GO) is an international standard classification system of gene function. GO can be divided into three parts: molecular function (MF), biological process (BP) and cellular component (CC). GO enrichment was characterized by p value less than 0.05. Biological processes mainly include cell metabolism, organic ring compound metabolism, compound metabolism containing nuclear bases, nitrogen compound metabolism, etc(Fig. 2 B(a)). Cell components include : intracellular organelles, cytoplasm, membrane-bound organelles; the molecular functions include protein binding, ion binding, DNA binding, RNA polymerase II transcription function, and oxidoreductase activity. In organisms, different genes perform their biological functions in coordination with each other, and Pathway significant enrichment can identify the most important biochemical metabolic pathways and signal transduction pathways in which candidate target genes are involved. KEGG ( Kyoto Encyclopedia of Genes and Genomes ) is the main public database on Pathway. Pathway dominance enrichment analysis took KEGG Pathway as the unit, and applied hypergeometric test to identify the pathway that was significantly enriched in candidate target genes compared with the whole genome background. Similarly, KEGG pathway enrichment was significantly enriched with p value less than 0.05. LncRNA KEGG enrichment results showed that lncRNAs involve metabolic pathways, phagocytosis, cytochrome P450 metabolic xenobiotics, antigen processing and display, glycine / serine and threonine metabolism, glycosphingolipid biosynthesis-lactate and neolactate series, and cGMP-PKG signaling pathways (Fig. 2 B(b)). The results of mRNA GO functional enrichment showed that the biological processes involved mainly include the tissue or biological occurrence of cell components, intracellular organelles, and phosphate-containing compound metabolism. Cell components include cytoskeleton, cytoplasm, membrane-bound organelles and cell connections ; molecular function is similar to lncRNA, including protein binding, ion binding, cytoskeleton protein binding, molecular function regulation and cell adhesion molecule binding (Fig. 2 C(a)). mRNA KEGG enrichment results showed that mRNA involved in the pathway of amino sugar and nucleotide sugar metabolism, adhesion connection, actin cytoskeleton regulation, cancer-related pathways, focal adhesion and Rap1 signaling pathway (Fig. 2 C(b)). LncRNAs have rich biological functions and are widely involved in various important physiological processes of organisms. They can regulate the expression of target genes at the transcriptional and post-transcriptional levels, and identify differential functional pathways generated by different treatments. There are various mechanisms by which lncRNAs regulate target genes. The most common ways of regulating target genes are co-location and co-expression target gene regulation. Co-location (co-location) means that lncRNA may have regulatory effects on nearby protein-coding genes, and the analysis is done by searching for genes within 100kb upstream and downstream of lncRNA; co-expression (co-expression) means that lncRNA acts on a distant location after transcription The mode of action of the target genes was analyzed by the expression correlation among multiple samples.Through the above analysis, we screened out multiple lncRNAs that can regulate PIM2 (Fig. 2 D). Expression of PCSK1N-202 in CD34 + cells from MDS patients and correlation with PIM-2 To verify the sequencing results, we detected the expression levels of LncRNA PCSK1N-202 in bone marrow CD34 + cells of 40 MDS patients, 24 AML patients and 31 healthy controls by RT-PCR. The expression level of PCSK1N-202 was 11.26 (0.92,153.70) in MDS group, 135.00 (14.37,1442.00) in AML group and 0.65 (0.178,4) in healthy control group. The expression level of PCSK1N-202 in MDS and AML group was significantly higher than that in healthy control group, and that in AML group was significantly higher than that in MDS group (Fig. 3 A). According to IPSS-R risk stratification, MDS patients were divided into group A (extremely low-risk group, low-risk group and medium-risk group) and group B (high-risk group and extremely high-risk group). The expression level of PCSK1N-202 in group B was significantly higher than that in group A (Fig. 3 B).The expression levels of PIM2 and PCSK1N-202 RNA in CD34 + cells of the same patient were detected by RT-PCR. Spearman correlation analysis was used to analyze the correlation between PIM2 and PCSK1N-202 RNA expression, and the results showed that there was a significantly positive correlation between them ( Spearman r = 0.56, p = 0.0165 ) (Fig. 3 C). This result suggests that lncRNA PCSK1N-202 may have a positive regulatory relationship with PIM2. To validate the regulation of lncRNA PCSK1N-202 to PIM2,the cellular localization of LncRNA PCSK1N-202 was carried out by using RNA fluorescence in situ hybridization which indicated that PCSK1N-202 is distributed in the nucleus and cytoplasm(Fig. 3 D). Down regulation of PCSK1N-202 induced MDS cell apoptosis by PIM2/HIF-1α In order to verify the relationship between lncRNA PCSK1N-202 and PIM2, we constructed lentiviruses (LV-PCSK1N-202-72, LV-PCSK1N-202-73, LV-PCSK1N-202-74) and empty viruses that interfere with the expression of PCSK1N-202. SKM-1 was transfected with these four lentiviruses. Through the preliminary experiment we determined the transfection conditions for MOI = 50, HiTransG P transfection enhancer, transfection efficiency was observed after 72 hours (Fig. 4 A-B). The expression level of PCSK1N-202 was detected by RT-PCR (Fig. 4 C), and the results showed that all three lentiviruses could knock down PCSK1N-202.The apoptosis of SKM-1 cells transfected with lentivirus LV-PCSK1N-202-72 / 73 / 74 was detected by Annexin V / 7-AD kit. The results showed that the apoptotic cells of LV-PCSK1N-202-72 / 73 / 74 were significantly increased compared with the empty virus group (Fig. 4 D-E). The results showed that lncRNA PCSK1N-202 regulates apoptosis.EdU kit was used to detect the proliferation of SKM-1 cells after lentivirus LV-PCSK1N-202–72 / 73 / 74. The results showed that the cell proliferation of LV-PCSK1N-202–72 / 73 / 74 was significantly decreased compared with that of the empty virus group ( Fig. 4 F-G). The results showed that lncRNA PCSK1N-202 could up-regulate cell proliferation.Western blot was used to detect the levels of PIM2 and HIF-1α protein in the cells after lentivirus LV-PCSK1N-202–72 / 73 / 74 knocked down SKM-1 PCSK1N-202. The results showed that PIM2 and HIF-1α decreased significantly after knocking down PCSK1N-202 (Fig. 4 H). Discussion The clinical presentation of patients with MDS varies, and the intuitive difference between patients with low-risk MDS patients and high-risk MDS patients is the number of primitive cells in the bone marrow. In terms of cell proliferation and cell death, patients with low-risk MDS mainly show ineffective hematopoiesis due to increased cell death. Studies have shown that the causes of cell death in patients with low-risk MDS are non-inflammatory and inflammatory factors; non-inflammatory factors such as apoptosis [ 26 ], while inflammatory factors include cell scorching and necrosis[ 27 , 28 ]. PIM kinase is mainly regulated by various cytokines and growth factors at the transcription and translation levels, including TNF-α、IL-2(interleukin-2)、IL-3、IL-6, GM-CSF (granulocyte-macrophage colony-stimulating factor) and G-CSF (granulocyte-colony stimulating factor)[ 29 – 31 ]。The stability and function of PIM kinase are related to the binding of heat shock protein ( Hsp ) 90[ 32 ]. Although the functions of these three kinases are similar, their tissue distributions are different. PIM1 and PIM2 are mainly expressed in hematopoietic cells[ 33 , 34 ], but PIM-3 is highly expressed in brain, kidney and epithelial cells[ 35 ]. Studies have showed that PIM2 is a downstream target of the NF-κB pathway, and there are some views that PIM2 can also act as an upstream protein to regulate the NF-κB pathway. A recent study found that there is a feedback loop between PIM2 and NF-κB signaling[ 11 ]. Our previous studies in leukemia cells ( K562 ), multiple myeloma cells ( RPMI-8226 ) and lung cancer cells ( A549, H1299 ) found that down-regulation of PIM2 could block the cell cycle at G0 / G1 phase by increasing the expression of P21. After knocking down the expression of PIM2, the expression level of NF-kB decreased[ 36 ], These suggested that PIM2 affected the proliferation of tumor cells by regulating the cell protein p21 and NF-kB cell signaling pathway. In myeloma cell lines, zoledronic acid synergistically inhibited the growth of myeloma cells by combining with bortezomib to suppress PIM2 expression[ 37 ], It suggested that PIM2 may be involved in regulating tumor cell proliferation by modulating the cell cycle. LncRNA was first discovered in 1990, when it was thought to be largely incapable of translating proteins, but its function was not clear [ 38 ]. Subsequently, it was found that lncRNAs can affect cell growth and differentiation through the regulation of chromatin modifications, gene expression [ 39 ]. According to the ENCODE (Encyclopedia of DNA Elements) project, it is estimated that the human genome encodes more than 28,000 different long non-coding RNAs (lncRNAs), many of which are still undiscovered and remain to be annotated[ 40 ]. In recent years there has been an increasing number of studies on lncRNAs, especially in the field of oncology. In hematologic tumors, some differentially expressed lncRNAs have also been identified and some of them may be used as diagnostic or prognostic indicators. With the development of high-throughput sequencing technology, the research on lncRNAs has become more and more advanced. In this study, we first analyzed the publicly accessible TCGA database and analyzed PIM2 expression levels by RNA sequencing datasets of AML as well as clinical data, and our findings suggested that elevated PIM2 expression might reduce the prognostic survival time of a subset of patients with myeloid malignancies. It has been found in our previous study that PIM2 is highly expressed in CD34 + cells derived from the bone marrow of MDS patients. It may be a potential biomarker for the diagnosis of MDS. We therefore speculated that elevated PIM2 expression may also correlate with poor prognosis in MDS patients.[ 36 ]. In addition, we analyzed the lncRNA expression profiles of bone marrow CD34 + cells in MDS patients and sAML patients by high-throughput sequencing technology. The results showed significant differences in lncRNA expression profiles between the two groups, and moreover, 1173 lncRNAs (of which 648 were up-regulated and 525 were down-regulated) and 326 mRNAs (of which 125 were up-regulated and 201 were down-regulated) were detected that were significantly altered in sAML compared with the MDS group. To investigate the functions of these differential genes, we performed GO and KEGG enrichment analysis of differential genes. lncRNA GO enrichment showed that: the biological processes involved in lncRNAs mainly include cellular metabolic processes, organic cyclic compound metabolic processes, nucleobase-containing compound metabolic processes, nitrogen compound metabolic processes, etc.; the cellular components include: intracellular organelle part, cytoplasmic part, membrane The molecular functions include: protein binding, ion binding, DNA binding, RNA polymerase II transcriptional function, oxidoreductase activity, etc. ncRNA KEGG enrichment results show: lncRNA involved in pathways such as metabolic pathways, phagosome, cytochrome P450 metabolism xenobiotics, antigen processing and presentation, glycine/serine and threonine metabolism, glycosphingolipid biosynthesis-lactate and neo-lactate series, and cGMP-PKG signaling pathway. mRNA GO functional enrichment results show involved in biological processes The cellular components include: cytoskeleton, cytoplasmic part, membrane-bound organelles and cell junctions, etc. The molecular function part is similar to lncRNA, including: protein binding, ion binding, cytoskeletal protein binding, molecular function regulation and cell adhesion molecule binding, etc. The mRNA KEGG enrichment results showed that the mRNA involved in pathways such as amino and nucleotide sugar metabolism, adhesion junctions, regulation of actin cytoskeleton, cancer-related pathways, focal adhesions and Rap1 signaling pathway. LncRNA KEGG enrichment results show: lncRNA involved in pathways such as metabolic pathways, phagosome, cytochrome P450 metabolism xenobiotics, antigen processing and presentation, glycine/serine and threonine metabolism, glycosphingolipid biosynthesis-lactate and neo-lactate series, and cGMP-PKG signaling pathway. mRNA GO functional enrichment results show involved in biological processes The cellular components include: cytoskeleton, cytoplasmic part, membrane-bound organelles and cell junctions, etc. The molecular function part is similar to lncRNA, including: protein binding, ion binding, cytoskeletal protein binding, molecular function regulation and cell adhesion molecule binding, etc. The mRNA KEGG enrichment results showed that the mRNA involved in pathways such as amino and nucleotide sugar metabolism, adhesion junctions, regulation of actin cytoskeleton, cancer-related pathways, focal adhesions and Rap1 signaling pathway. In order to verify this hypothesis, we knocked down lncRNA PCSK1N-202 of SKM-1 cell line by lentivirus interference technology to detect cell proliferation and apoptosis. The results showed that knocking down PCSK1N-202 could lead to decreased cell proliferation and increased apoptosis. Western blot showed that PIM2 and HIF-1α decreased significantly after knocking down PCSK1N-202. This result suggested that lncRNA PCSK1N-202 could promote the malignant proliferation of MDS CD34 + cells and inhibit their apoptosis by up-regulating PIM2 / HIF-1α. In conclusion, lncRNAs play a role in the malignant proliferation of bone marrow hematopoietic stem cells in MDS patients. lncRNA PCSK1N-202 can promote the malignant proliferation of MDS CD34 + cells and inhibit their apoptosis by up-regulating PIM2 / HIF-1α. Conclusion Through high-throughput sequencing, we found that the differential lncRNA PCSK1N-202 of CD34 + cells in sAML and MDS patients can participate in the proliferation of CD34 + cells in MDS patients by regulating PIM2/HIF-1α. The expression level of PIM2 in bone marrow CD34 + cells of MDS patients was significantly higher than that of healthy controls. Meanwhile, lncRNA PCSK1N-202 can regulate the proliferation of CD34 + cells in the bone marrow of MDS patients through the PIM2/HIF-1α cell signaling pathway. Declarations Ethical Approval Ethics Committee of Tianjin Medical University General Hospital permitted this project. The scanned copy of the ethics document has been uploaded. Competing interests All authors declare no conflict of interest. Author contributions Rong Fu and Zhaoyun Liu designed the project and proofread the manuscript. Mengyue Tian and Yue Jia carried out the experiments, Yixuan Guo analysed the data and finished the manuscript. Nanhao Meng and Lixiang Duan participated in the experimental work. All authors checked and approved the final manuscript. Fundings ： This work was supported by the National Natural Science Foundation of China Youth Project (grant no. 81900131), the Tianjin Municipal Natural Science Foundation (grant no. 18JCQNJC80400), the Tianjin Education Commission Research Project (grant no. 2018KJ043), the Tianjin Education Commission Research Project (grant no. 2018KJ045), and the Tianjin Science and Technology Planning Project (no. 20YFZCSY00060).Tianjin Municipal Health Commission Youth Project（grant no. TJWJ2021QN001)；Medjaden Academy & Research Foundation for Young Scientists (Grant No. MJR20221011);Tianjin Key Medical Discipline(Specialty) Construction project. In addition, some of the contents of this manuscript have been published by the type of E-Poster Presentation on EHA, the author is Liu Zhaoyun, Tian Mengyue, Fu Rong (Correspondence author). click the following link for more details: https://library.ehaweb.org/eha/2021/eha2021-virtual-congress/325653/zhaoyun.liu.lncrna.pcsk1n-202.promotes.cd342Bcell.proliferation.via.pim2.hif-1.html?f=. Availability of data and materials N/A. References Adès L, Itzykson R, Fenaux P. Myelodysplastic syndromes[J]. Lancet (London, England), 2014;383(9936):2239–2252. Papaemmanuil E, Gerstung M, Malcovati L, et al. Clinical and biological implications of driver mutations in myelodysplastic syndromes[J]. Blood, 2013;122(22):3616–3627; quiz 3699. Makishima H, Yoshizato T, Yoshida K, et al. Dynamics of clonal evolution in myelodysplastic syndromes[J]. Nature genetics, 2017;49(2):204–212. Hirsch CM, Nazha A, Kneen K, et al. Consequences of mutant TET2 on clonality and subclonal hierarchy[J]. 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Sustained expression of the pim-1 kinase is specifically induced in myeloid cells by cytokines whose receptors are structurally related[J]. Oncogene, 1992;7(4):727–732. Pratt WB. The role of the hsp90-based chaperone system in signal transduction by nuclear receptors and receptors signaling via MAP kinase[J]. Annual review of pharmacology and toxicology, 1997;37:297–326. Mikkers H, Nawijn M, Allen J, et al. Mice deficient for all PIM kinases display reduced body size and impaired responses to hematopoietic growth factors[J]. Molecular and cellular biology, 2004;24(13):6104–6115. Bachmann M, Möröy T. The serine/threonine kinase Pim-1[J]. The international journal of biochemistry & cell biology, 2005;37(4):726–730. Feldman JD, Vician L, Crispino M, et al. KID-1, a protein kinase induced by depolarization in brain[J]. The Journal of biological chemistry, 1998;273(26):16535–16543. Liu Z, Liu H, Yuan X, et al. Downregulation of Pim-2 induces cell cycle arrest in the G(0)/G(1) phase via the p53-non-dependent p21 signaling pathway[J]. Oncology letters, 2018;15(4):4079–4086. Jena PV, Safaee MM, Heller DA, et al. DNA-Carbon Nanotube Complexation Affinity and Photoluminescence Modulation Are Independent[J]. ACS applied materials & interfaces, 2017;9(25):21397–21405. Brannan CI, Dees EC, Ingram RS, et al. The product of the H19 gene may function as an RNA[J]. Molecular and cellular biology, 1990;10(1):28–36. Bhan A, Mandal SS. LncRNA HOTAIR: A master regulator of chromatin dynamics and cancer[J]. Biochimica et biophysica acta, 2015;1856(1):151–164. Tragante V, Moore JH, Asselbergs FW. The ENCODE project and perspectives on pathways[J]. Genetic epidemiology, 2014;38(4):275–280. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3177358","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":221571433,"identity":"e0add2a3-e3b6-42b2-a5ea-5efdd48532a7","order_by":0,"name":"Zhaoyun Liu","email":"","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhaoyun","middleName":"","lastName":"Liu","suffix":""},{"id":221571434,"identity":"ba164544-2b94-492d-93f1-0e2d9ac8a43f","order_by":1,"name":"Mengyue Tian","email":"","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mengyue","middleName":"","lastName":"Tian","suffix":""},{"id":221571435,"identity":"698611a7-0570-403b-a4da-33340bbb1cfc","order_by":2,"name":"Yue Jia","email":"","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Jia","suffix":""},{"id":221571436,"identity":"22262cf0-b629-47f0-b448-a2b6576791c5","order_by":3,"name":"Yixuan Guo","email":"","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yixuan","middleName":"","lastName":"Guo","suffix":""},{"id":221571437,"identity":"f242c00b-92ec-484e-8178-cce86c1379cf","order_by":4,"name":"Xianghong Zhao","email":"","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xianghong","middleName":"","lastName":"Zhao","suffix":""},{"id":221571438,"identity":"53a0d911-f4b2-4871-bc3a-08d2e451fbee","order_by":5,"name":"Nanhao Meng","email":"","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nanhao","middleName":"","lastName":"Meng","suffix":""},{"id":221571439,"identity":"ab2f948e-2e90-40c6-8ee8-57a9e11bfce2","order_by":6,"name":"Lixiang Duan","email":"","orcid":"","institution":"Yuncheng Central Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lixiang","middleName":"","lastName":"Duan","suffix":""},{"id":221571440,"identity":"f182061f-8fde-4ef1-9aa2-72aff1a3c883","order_by":7,"name":"Rong Fu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYBAC9gYwZWPHz958ACJ0gIAWHoiCtGTJnmOJDaRoOcy4YUaOIZFaJHIfPi74lcZsIJHz/dHNNgY5vhsJjJ8L8GpJNzae2WfDZ87zdmNzbhuDseSNBGbpGXi02EuksUnz9qQxW7bngrUkbriRwMbMg9cWsBagXw7kPARpqSdOC88PoJYTOYwgLQkGBLXwPGM25m0AB7Lh7JxzEoYzzzxslsarhT2N8THPH3BUPvicU2Yjz3c8+eBnfFrAgLENzpQAcRsIaQCCP0SoGQWjYBSMgpELAPhhTATlHmAQAAAAAElFTkSuQmCC","orcid":"","institution":"Tianjin Medical University General Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Rong","middleName":"","lastName":"Fu","suffix":""}],"badges":[],"createdAt":"2023-07-17 09:36:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3177358/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3177358/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":40823296,"identity":"6e85d92d-d0fe-4ff4-bf03-7db77afe53aa","added_by":"auto","created_at":"2023-07-31 13:58:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":136958,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHigh PIM2 expression levels correlate with lower overall survival in myeloid malignancies. \u003c/strong\u003eA. consensus clustering cumulative distribution function (CDF) and relative change in the area under the CDF curve (CDF Delta area). The relative change in area under the cumulative distribution function (CDF) curves when cluster number varying from k-1 to k. B. consistency of clustering results heatmap (k = 6), Rows and columns represent samples, the different colors represent different types (Cluster 1 to Cluster 6). C. Cluster 2 had much higher levels of PIM2 expression than Cluster 1 and Cluster 5. D. Kaplan-Meier survival analysis of the Cluster 1, 2, and 5, comparison among different groups was made by log-rank test. 95% CL represents the HR confidence interval; Median time represents the time corresponding to survival in different groups at 50% (median survival time) in years. The median overall survival time of Cluster 2 with high expression of PIM2 was significantly shorter compared to Cluster 1 and Cluster 5.\u003c/p\u003e\n\u003cp\u003e****p \u0026lt; 0.0001, asterisks (*) stand for significance levels. The statistical difference of two groups was compared through the Wilcox test, significance difference of three groups was tested with Kruskal-Wallis test.\u003c/p\u003e","description":"","filename":"FIG.1.png","url":"https://assets-eu.researchsquare.com/files/rs-3177358/v1/bc6c7900a4ba16234cdf66fb.png"},{"id":40823300,"identity":"da1d0784-789a-4715-a6f3-e64c91ea543a","added_by":"auto","created_at":"2023-07-31 13:58:38","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":275417,"visible":true,"origin":"","legend":"\u003cp\u003eBone marrow CD34+ cell lncRNA sequencing and bioinformatic analysis. A(a). Volcano map of lncRNA differential genes；(b). Volcano map of mRNA differential genes；(c). lncRNA clustering heat map；(d). Heat map of mRNA clustering. The log2FoldChange of gene expression between different samples or comparison combinations is represented by the horizontal coordinates of volcanic map. The greater the absolute value of the horizontal coordinates, the greater the expression change between the two comparison combinations. The ordinate represents the significant level of expression differences. The up-regulated genes were expressed as red dots, and the down-regulated genes were expressed as green dots. The blue dots were genes without significant changes. Cluster hot map : the horizontal coordinate is the sample, the ordinate is the differential gene. The gene is clustered according to the expression similarity on the left side, and each sample is clustered according to the similarity of the expression spectrum above. The expression level is gradually increased from blue to red, and the number is the relative expression level after homogenization.B.(a) lncRNA GO enrichment histogram；(b) lncRNA KEGG enrichment scatter plot. C. (a)mRNA GO enrichment histogram；(b) mRNA KEGG enrichment scatter plot. The horizontal coordinate of the volcano plot indicates the expression fold change (log2FoldChange) between different samples or comparative combinations of genes. Up-regulated genes are shown as red points, down-regulated genes are shown as green points, and blue points are genes that did not change significantly. The horizontal coordinates of the clustering heat map are the samples, the vertical coordinates are the differential genes, the left side clusters the genes according to the degree of expression similarity, the upper side clusters each sample according to the degree of similarity of expression profiles, the expression is gradually up-regulated from blue to red, and the numbers are the relative expressions after homogenization.D. lncRNA targeting PIM2 gene.\u003c/p\u003e","description":"","filename":"FIG.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3177358/v1/40b2ef5748c2d80e88039b7b.jpg"},{"id":40825361,"identity":"b90465ec-0fc4-4c2b-b38e-d54b06052171","added_by":"auto","created_at":"2023-07-31 14:06:38","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":82116,"visible":true,"origin":"","legend":"\u003cp\u003eExpression of PCSK1N-202 of MDS patients and correlation with PIM-2. A. The expression of PCSK1N-202 in CD34\u003csup\u003e+\u003c/sup\u003e cells of MDS, AML and HD patients. B.The expression of PCSK1N-202 correlated with MDS survival according to IPSS-R risk stratification(group A (extremely low-risk group, low-risk group and medium-risk group) and group B (high-risk group and extremely high-risk group)). C.LncRNA PCSK1N-202 was a significantly positive correlated with PIM2. D. The distribution of LncRNA PCSK1N-202\u0026nbsp; is\u0026nbsp; in the nucleus and cytoplasm by fluorescence in situ hybridization.\u003c/p\u003e","description":"","filename":"FIG.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3177358/v1/4ab829dff010273ef266693c.jpg"},{"id":40823298,"identity":"ea3b65e8-e120-423f-a48f-63603b98c9e5","added_by":"auto","created_at":"2023-07-31 13:58:38","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":408153,"visible":true,"origin":"","legend":"\u003cp\u003eknockdown of PCSK1N-202 inhibits the proliferation of MDS cell by PIM2/HIF-1α. A. The transfection results under fluorescence microscope. B. Detection of transfection efficiency by flow cytometry. C. LncRNA PCSK1N-202 knock-down efficiency. D. The apoptosis detection in SKM-1 cells after knockdown of LncRNA PCSK1N-202 by flow cytometry. E. Cell apoptosis after lentivirus LV-PCSK1N-202-72/73/74 knocked down PCSK1N-202 of SKM-1. F. Cell proliferation by flow cytometry. G. Cell proliferation after lentivirus LV-PCSK1N-202-72/73/74 knocked down PCSK1N-202 of SKM-1. H. Protein levels of PIM2 and HIF-1α in cells after SKM-1 - knocked down by lentivirus LV-PCSK1N-202-72/73/74.\u003c/p\u003e","description":"","filename":"FIG.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3177358/v1/838e09f37cd0446ae8ac00cc.jpg"},{"id":40825362,"identity":"ff47b18d-de1a-4501-b633-79342b5ada0f","added_by":"auto","created_at":"2023-07-31 14:06:38","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":168251,"visible":true,"origin":"","legend":"\u003cp\u003eThe mechanism of PCSK1N-202 involved in the malignant proliferation of CD34\u003csup\u003e+\u003c/sup\u003e cells in MDS patients by regulating PIM2/HIF-1α\u003c/p\u003e","description":"","filename":"FIG.5.png","url":"https://assets-eu.researchsquare.com/files/rs-3177358/v1/560c6fe0de0a9aadadb69afd.png"},{"id":41671428,"identity":"0cd983d9-17e1-4156-838c-e3c3f2f5c5f7","added_by":"auto","created_at":"2023-08-17 03:52:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1353394,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3177358/v1/6e073c69-918b-46b5-80c0-8b4aabdf6584.pdf"},{"id":40825360,"identity":"baa2915f-49b9-4031-8229-edd21e0f097f","added_by":"auto","created_at":"2023-07-31 14:06:38","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":30674,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-3177358/v1/7dc4ef86b56e4891c3bf7b93.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"LncRNA PCSK1N-202 regulates CD34 + hematopoietic cells proliferation in MDS patients via PIM2/HIF-1alpha","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMyelodysplastic syndrome (MDS) is a group of malignant clonal hematopoietic stem cell diseases characterized by ineffective hematopoiesis and pathological hematopoiesis resulting in a f and a high risk of transformation to acute myeloid leukemia (AML)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The use of new drugs of azacytidine, decitabine and lenalidomide has indeed played a role in delaying disease progression and improving clinical symptoms in some MDS patients, but it is still unable to completely improve the prognosis of patients. In particular, the conversion to acute myeloid leukemia in high-risk MDS patients remains an urgent problem. Therefore, exploring the molecular mechanisms related to the malignant proliferation of MDS hematopoietic stem cells may provide new therapeutic tools for MDS patients, prolonging their trans-AML cycle and survival cycle and improving their quality of life.\u003c/p\u003e \u003cp\u003eFor high-risk MDS patients and trans-AML patients, malignant proliferation of bone marrow hematopoietic stem cells is the most prominent feature. With the development and application of second-generation sequencing technology, more and more studies have confirmed that malignant clones of MDS are caused by multiple genetic mutations occurring sequentially. These mutations are involved in various cellular functions such as RNA splicing, chromatin modification, epigenetic regulation, DNA damage and stress response [\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] .\u003c/p\u003e \u003cp\u003ePIM(The proviral insertion site in Moloney murine leukemia virus) is a family of serine/threonine kinases with three members, PIM1, PIM2, and PIM3. PIM2 is highly homologous to PIM1 and PIM3, which have similar oncogenic functions [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Two PIM2 subtypes ( 34,40 kDa ) were detected in human cells, but 34 - kDa PIM2 subtype mainly played a role in tumor progression. PIM2 is highly expressed in many malignant tumors, such as breast cancer, lung cancer, liver cancer, brain cancer, renal cancer, prostate cancer, leukemia and multiple myeloma[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. As a serine / threonine kinase, PIM2 functions through phosphorylation of several substrates, including c-MYC, Notch1, Rela, p21, p27, BAD, PKM2, HK2 and TSC2[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. PIM kinase promotes cancer cell growth and migration by regulating cell cycle, apoptosis and proliferation. In acute leukemia, PIM2 inhibitors promote apoptosis and inhibit cancer cell proliferation in leukemic cells by decreasing the expression of c-Myc-(Ser62), 4E-BP1 (Thr36/Thr47) and the apoptotic proteins Bcl-2, Bcl-xL, XIAP[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. It has been shown that PIM2 and HIF-1α promote and induce each other in a hypoxic environment[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], leading to malignant proliferation of hepatocellular carcinoma cells. PIM2 enhances the stability of HSF1 protein by phosphorylating HSF1 Thr120 to induce PD-L1 expression and promotes the proliferation of breast cancer cells in cell and xenograft mouse models. The overexpression of PIM2 up-regulates HIF1α and VEGF, enhances angiogenesis, and causes the progression of hepatocellular carcinoma. In addition, the up-regulation of PIM2 can increase the expression of MMP9 and enhance the metastasis ability of hepatocellular carcinoma cells, which is crucial for the development of advanced hepatocellular carcinoma[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn increasing number of studies have shown that PIM kinases play a crucial role in a variety of tumors, and therefore PIM inhibitors have become a hot research topic as therapeutic targets [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. So far, PIM inhibitors have been used in clinical trials for the treatment of leukemia or multiple myeloma [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. PIM inhibitors have been shown to significantly inhibit the proliferation of B-ALL cell lines by blocking the cell cycle in the G0/G1 phase, and to induce apoptosis by mediating the JAK2/STAT3 pathway via HO-1. A clinical trial of PIM inhibitors in patients with multiple myeloma showed that PIM447, a novel pan-PIM inhibitor, showed strong synergistic effects with different standard treatment regimens such as bortezomib\u0026thinsp;+\u0026thinsp;dexamethasone, lenalidomide\u0026thinsp;+\u0026thinsp;dexamethasone and pomalidomide\u0026thinsp;+\u0026thinsp;dexamethasone[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Thus PIM2 inhibitors may become an important therapeutic strategy for targeting MM cell-bone marrow interactions[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOnly 2% of RNA in the human genome is involved in protein transcription and translation, while the remaining 98% does not have protein-coding functions and is therefore collectively referred to as non-coding RNA. LncRNA (long non-coding RNA) is an RNA that does not encode proteins and \u0026gt;\u0026thinsp;200 nucleotides in length[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The human genome has over 15,000 lncRNAs that play a role in many life activities and can function in a variety of ways. LncRNAs can recruit different components of the chromatin remodeling complex to alter chromatin organization[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. LncRNAs can affect cellular function through a range of mechanisms, and it is not surprising that these molecules are utilized in different types of cancers. They have been shown to regulate cancer cell proliferation, migration, immune escape and apoptosis, as well as other common features of cancer progression[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. LncRNA analysis by NLCFA technique in 10 cases of MDS (RAEB-2) versus 6 normal controls revealed that the expression levels of up to 51 long-chain non-coding RNAs were different [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In addition, four LncRNAs (TC07000551.hg.1,TC08000489.hg.1, TC02004770.hg.1, and TC03000701.hg.1) were found to be associated with overall survival and risk stratification in MDS patients by LncRNA assays in 176 MDS patients, and detection of these LncRNAs in patients suggesting poor prognosis[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In addition, overexpression of LncRNA CCAT2 in mice promoted tumorigenesis in MDS mice, and increased levels of CCAT2 expression were found in MDS patients [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Neal S. Young[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] also found 2892 LncRNAs in MDS by single-cell gene sequencing, of which 2084 were unknown LncRNAs, and further found that LncRNAs play an important role in hematopoietic stem cell differentiation. It is suggested that LncRNAs play an important role in the development of MDS.\u003c/p\u003e \u003cp\u003eHere,we find PIM2 expression levels correlate with overall survival in myeloid malignancies,and the LncRNA PCSK1N-202 may through PIM2 / HIF-1α regulate the proliferation of CD34\u0026thinsp;+\u0026thinsp;cells in MDS.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003e The study was obtained from 54 patients who visited the Department of Hematology, General Hospital of Tianjin Medical University from July 2017 to April 2018 by primary diagnosis, including 36 patients with MDS,18 patients with AML,23 healthy donors(HD). MDS patients all met the diagnostic criteria established by WHO 2016 and were typed according to WHO 2016. The basic information of the study subjects is detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatients and clinical characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNumber of samples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMDS patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.4(30\u0026ndash;84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2016 WHO type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eSLD\u003c/p\u003e \u003cp\u003eMLD\u003c/p\u003e \u003cp\u003eRS\u003c/p\u003e \u003cp\u003eEB-1\u003c/p\u003e \u003cp\u003eEB-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.6(59\u0026ndash;67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.5(56\u0026ndash;84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.9(30\u0026ndash;66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.1(44\u0026ndash;75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAML patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.9(20\u0026ndash;78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.7(23\u0026ndash;79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: SLD, MDS with single lineage dysplasia; MLD, MDS with multilineage dysplasia; RS, MDS with ringed sideroblast; EB, MDS with excess blasts;AML, Acute myeloid leukemia.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eCD34\u0026thinsp;+\u0026thinsp;cells sorting\u003c/h2\u003e \u003cp\u003eBone marrow was obtained from MDS patients, AML patients and healthy donors. Bone marrow mononuclear cells were isolated using density gradient centrifugation(Solarbio, Beijing), CD34\u003csup\u003e+\u003c/sup\u003e cells were isolated in MACS(Miltenyi Biotec, Germany) using the CD34\u003csup\u003e+\u003c/sup\u003e Cell Isolation Kit(Miltenyi Biotec, Germany) according to the instructions, and CD34\u003csup\u003e+\u003c/sup\u003e cell purity was determined to be \u0026gt;\u0026thinsp;95% by flow cytometry.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eBiological information analysis of CD34\u003csup\u003e+\u003c/sup\u003e cells by lncRNA sequencing:\u003c/h2\u003e \u003cp\u003eThe above obtained CD34\u003csup\u003e+\u003c/sup\u003e cells were placed in Trizol(Thermo Fisher Scientific, America) to obtain total RNA. Total RNA was sequenced and bioinformatically analyzed (Shanghai GeneMed Technology Co., Ltd.). The experimental procedure includes: Total RNA sample detection, rRNA removal, double-stranded cDNA synthesis, end repair, addition of sequencing junction, fragment selection, degradation of cDNA second strand, PCR enrichment, library quality control, and sequencing on the machine. The sequencing platform was novaseq 6000.The raw reads per sample has been listed in table S1. GO and KEGG enrichment analysis of target genes of differentially expressed lncRNAs was implemented by the cluster Profiler R package, in which gene length bias was corrected.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eClinical outcome analysis\u003c/h2\u003e \u003cp\u003eThe TCGA dataset (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portal.gdc.cancer.gov/repository\u003c/span\u003e\u003cspan address=\"https://portal.gdc.cancer.gov/repository\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to get RNA-sequencing expression profiles and clinical information for AML[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The maximum number of clusters is 6, and 80 percent of the whole sample is drawn 100 times, using the ConsensusClusterPlus R package (v1.54.0)[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], clusterAlg = \"hc,\" inner Linkage='ward. D2'. For clustering heatmaps, use the R software package pheatmap (v1.0.12, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cran.r-project.org/web/packages/pheatmap/index.html\u003c/span\u003e\u003cspan address=\"https://cran.r-project.org/web/packages/pheatmap/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The current-release (V8) GTEx datasets were obtained from the GTEx data portal website (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gtexportal.org/home/datasets\u003c/span\u003e\u003cspan address=\"https://www.gtexportal.org/home/datasets\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The Kaplan-Meier survival analysis was performed by the R program ggplot2. All the analysis methods and R package were implemented by R software (version 4.0.3). P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eReal-Time Polymerase Chain Reaction Analysis (RT-PCR):\u003c/h2\u003e \u003cp\u003eCD34\u003csup\u003e+\u003c/sup\u003e T cells were added to trizol to extract total RNA, and reverse transcribed cDNA was prepared according to the instructions of the Tiangen Reverse Transcription Kit(Tiangen, Beijing), and placed in an IQ5 real-time fluorescence quantitative PCR instrument using the SuperReal PreMix Plus (SYBR Green) system, and GAPDH was used as an internal reference to assess the relative expression of each target gene according to 2\u003csup\u003e\u0026minus;ΔΔCT\u003c/sup\u003e method. The sequences of cDNA primers (Biotech Bioengineering Co., Ltd.) designed for the target genes PIM2, HIF-1α, IDH1 and internal reference genes are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eqRT-PCR primer sequences\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimer sequences (5\u0026prime;-3\u0026prime;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIF-1α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward-ACG TTC CTT CGA TCA GTT GTC ACC\u003c/p\u003e \u003cp\u003eReverse-GGC AGT GGT AGT GGT GGC ATT AG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDH-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward-TCA GTG GCG GTT CTG TGG TAG AG\u003c/p\u003e \u003cp\u003eReverse-CAT CCT TGG TGA CTT GGT CGT TGG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward-TTG GGA AGG AAT GGT AGA TG\u003c/p\u003e \u003cp\u003eReverse-CAG GAG AAC AAA CAG CAA GC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGAPDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward-GGA GCG AGA TCC CTC CAA AAT\u003c/p\u003e \u003cp\u003eReverse-GGC TGT TGT CAT ACT TCT CAT GG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCell culture :\u003c/h2\u003e \u003cp\u003eThe cell line SKM1 used in this experiment was purchased from the National Biomedical Experimental Cell Library, and the whole culture process was completed in the sterile ultra-clean platform. The medium for SKM-1 was RPMI 1640(Solarbio, Beijing) containing 15% fetal bovine serum(Gibco, America). Planted at a density of 1х10\u003csup\u003e6\u003c/sup\u003e/ml in T25 flask(Corning, America) and cultured in 37\u0026deg;, 5%CO\u003csub\u003e2\u003c/sub\u003e incubator. When the cell density reached about 90%, the cell suspension was sucked into 15 ml sterile centrifuge tube, 800\u0026ndash;1000 rpm, centrifuged for 5 minutes. Discard the supernatant and add 2 times fresh medium into two culture flasks. And use this passaged cell line for subsequent experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSiRNA knock-down :\u003c/h2\u003e \u003cp\u003eThe number of cells in each well was controlled to be 4\u0026thinsp;~\u0026thinsp;8х10\u003csup\u003e5\u003c/sup\u003e in the 24-well plate, and the PIM2 targeted siRNA(GenePharma, Shanghai) was transfected with Lipofectamine 2000(Invitrogen, America). siRNA was diluted with 50 \u0026micro;L opti-MEM(Solarbio, Beijing), and 1 \u0026micro;L lipofectamine 2000 was added to 50 \u0026micro;L opti-MEM for dilution to prepare the transfection complex. Add the transfected complexes to the cultured cells and shake them gently. Cultured in 37℃, 5% CO\u003csub\u003e2\u003c/sub\u003e incubator for 48 hours and harvested for subsequent experiments.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eLentiviral transfection:\u003c/h2\u003e \u003cp\u003eA total of 8mL SKM-1 cell suspension with a density of 1х10\u003csup\u003e5\u003c/sup\u003e/mL was prepared using a complete medium, and the experiment was divided into four groups. 2mL of each well was added into a six-well plate, and four lentiviruses LV-PCSK1N-202-72/73/74 and con313 were added respectively ( Shanghai Jikai Gene Medical Technology Co., Ltd.). The cells were cultured in a 37\u0026deg;, 5% CO\u003csub\u003e2\u003c/sub\u003e cell incubator for 24 hours. The cells in each well were collected into the EP tube and centrifuged at 200 хg for 2 min. The supernatant was removed and replaced with a fresh medium. After gently blowing and mixing, the cells were put back into the incubator. The transfection efficiency was observed by fluorescence microscope and flow cytometry 72 hours after infection. Appropriate amount of cells were collected for subsequent experiments.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eWestern Blot\u003c/h2\u003e \u003cp\u003eProteins were extracted with lysis buffer. after SDS-PAGE, the samples were transferred to PVDF membranes(Easybio, Beijing). Next, the membranes were closed with 5% skim milk, and after membrane incubation with dilute antibody at 1:1000 concentration(CST, America), the membranes were rinsed with TBST(Solarbio, Beijing) and HRP-coupled di-incubated with dilute antibody༈CST, America༉ at 1:5000 concentration for 1 hour. After rinsing with TBST, a luminescent solution was prepared by thoroughly mixing liquid A and liquid B from the ECL chemiluminescence kit(Cell Signaling Technology, America), added to the PVDF membrane, and subsequently exposed in a fluorescence imager.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCell proliferation assay.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eConfigure EdU working solution and add 1 ml of cell suspension in a 6-well plate. Place the six-well plate in a cell incubator and incubate the cells for 2 hr. Collect the cells and fix them for 15 min at room temperature using 1 ml of fixative solution (paraformaldehyde) and wash. Add 1 ml of permeabilization solution (PBS containing 0.3% Triton X-100) (Solarbio, Beijing) to each well and incubate for 15 min at room temperature and wash. Configure Click reaction solution, mix with cell blowing and incubate for 30 min at room temperature protected from light.After washing, fluorescence detection was performed on a Beckman Coulter flow cytometer with APC fluorescence channel.\u003c/p\u003e \u003cp\u003e \u003cb\u003eApoptosis assay.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSKM-1 cells were collected by centrifugation at 2000 rpm for 5 min and washed. Dilute 10\u0026times;Binding Buffer tenfold, add 5\u0026micro;L of 7-AAD dye to 50\u0026micro;L of 1\u0026times;Binding Buffer, shake and mix, and incubate for 15min at room temperature, protected from light. 450\u0026micro;L of 1\u0026times;Binding Buffer was added and mixed, 5\u0026micro;L of Annexin V-PE(BD, America) is added and mixed, and incubated for 15min at room temperature, protected from light. The cells were detected by Beckman Coulter flow cytometer within 1 h. Annexin V was detected by the orange-red fluorescence channel of PE, and 7-AAD red fluorescence was detected by the PERCP channel.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLncRNA fluorescence in situ hybridization.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe probe sequence was designed according to the lncRNA base sequence (Shanghai Gema Pharmaceutical Technology Co., Ltd.), and the reagents were prepared according to the kit instructions. SKM-1 cells fixed in 4% paraformaldehyde were attached to glass slides with a slide machine. The dried cell pictures were placed in a 10cm dish, 100 \u0026micro;l of 0.5% Buffer A was added dropwise, the 0.5% Buffer A was discarded after incubation at room temperature for 15 minutes, and 500 \u0026micro;l of PBS was added dropwise to wash twice, 5 minutes each time. Add 100 \u0026micro;l of blocking solution dropwise to each slide and incubate at 37\u0026deg;C for 30 minutes. Discard the blocking solution, add 100 \u0026micro;l of buffer C dropwise, and incubate for 30 minutes in a 37\u0026deg;C cell incubator. Incubate Buffer E in a 73\u0026deg;C water bath for 30 minutes until the liquid becomes clear. The probe stock solution was diluted 100 times, placed in a 75\u0026deg;C water bath for denaturation for 10 minutes, then mixed with SA-CY3 at a ratio of 8:1, and incubated in a 37\u0026deg;C cell incubator for 30 minutes. Mix the probe working solution mixed in the previous step with 90 \u0026micro;l Buffer E. Place the glass slide horizontally in a wet box, drop the denatured probe mixture prepared in the previous step on the glass slide, cover with a cover glass, and incubate in a 37\u0026deg;C incubator for 12\u0026ndash;16 hours. The next day of hybridization, the glass slide was taken out, the cover glass was gently removed, the probe working solution was discarded, 100 \u0026micro;l of 0.1% buffer F was added, and washed at 37\u0026deg;C for 10 minutes. Discard 0.1% buffer F, add 100 \u0026micro;l of 2\u0026times;Buffer C, wash at 60\u0026deg;C for 10 minutes, and wash 3 times. 100 \u0026micro;l of DAPI working solution was added, and the cells were stained in the dark for 20 minutes. The DAPI working solution was removed and washed twice with PBS for 5 minutes each time. Add anti-quenching agent dropwise, cover with a coverslip, and observe under a fluorescence microscope.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis.\u003c/h2\u003e \u003cp\u003eSPSS software (version.19) and GraphPad Prism (version 7.0) statistical software were used for statistical analysis. Data were numerical variables, and if they conformed to a normal distribution, the three groups were compared with each other by one-way ANOVA; two groups were compared by unpaired t-test, and the data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. If they did not conform to normal distribution, Kruskal-Wallis test analysis (three groups of data) and Mann Whitney (two groups of data) tests were used, and the median and quartiles were used. Spearman correlation test was used for correlation analysis of the two data sets.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePIM2 expression levels correlate with overall survival in myeloid malignancies\u003c/h2\u003e \u003cp\u003eWe first analyzed the publicly accessible TCGA database and selected RNA-sequencing datasets of AML as well as clinical data. The RNA-sequencing data (n\u0026thinsp;=\u0026thinsp;151) were clustered into 6 subgroups based on immunological genes: Cluster 1 (n\u0026thinsp;=\u0026thinsp;49), Cluster 2 (n\u0026thinsp;=\u0026thinsp;31), Cluster 3 (n\u0026thinsp;=\u0026thinsp;15), Cluster 4 (n\u0026thinsp;=\u0026thinsp;17), Cluster 5 (n\u0026thinsp;=\u0026thinsp;31), and Cluster 6 (n\u0026thinsp;=\u0026thinsp;8) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e AB). Then we analyzed the PIM2 expression levels in different clusters and observed that PIM2 expression levels in Cluster 1, 2, and 5 were significantly different (p\u0026thinsp;=\u0026thinsp;1.3e-06). Specifically, PIM2 expression levels in Cluster 2 were substantially greater than those in Cluster 1 and 5, while there were no significant differences in Cluster 1 and Cluster 5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Further, we analyzed the prognostic survival of AML patients with Cluster 1, 2, and 5. Cluster 2 patients had a considerably worse overall survival than Cluster 1 and 5 patients (median time: 0.7, 2.2, and 1.8 years, respectively; p\u0026thinsp;=\u0026thinsp;0.0042) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Taken together, these findings suggest that elevated PIM2 expression may reduce prognostic survival time in a subset of patients with myeloid malignancies.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eHigh PIM2 expression levels correlate with lower overall survival in myeloid malignancies.\u003c/b\u003e A. consensus clustering cumulative distribution function (CDF) and relative change in the area under the CDF curve (CDF Delta area). The relative change in area under the cumulative distribution function (CDF) curves when cluster number varying from k-1 to k. B. consistency of clustering results heatmap (k\u0026thinsp;=\u0026thinsp;6), Rows and columns represent samples, the different colors represent different types (Cluster 1 to Cluster 6). C. Cluster 2 had much higher levels of PIM2 expression than Cluster 1 and Cluster 5. D. Kaplan-Meier survival analysis of the Cluster 1, 2, and 5, comparison among different groups was made by log-rank test. 95% CL represents the HR confidence interval; Median time represents the time corresponding to survival in different groups at 50% (median survival time) in years. The median overall survival time of Cluster 2 with high expression of PIM2 was significantly shorter compared to Cluster 1 and Cluster 5.\u003c/p\u003e \u003cp\u003e****p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, asterisks (*) stand for significance levels. The statistical difference of two groups was compared through the Wilcox test, significance difference of three groups was tested with Kruskal-Wallis test.\u003c/p\u003e \u003cp\u003e \u003cb\u003elncRNA sequencing and bioinformatic analysis of bone marrow CD34\u003c/b\u003e \u003csup\u003e \u003cb\u003e+\u003c/b\u003e \u003c/sup\u003e \u003cb\u003ecell in MDS patients and sAML patients\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo investigate the role of lncRNAs in malignant cloning of MDS CD34\u0026thinsp;+\u0026thinsp;cells and promotion of sAML patients, we performed lncRNA-seq analysis on CD34\u003csup\u003e+\u003c/sup\u003e cells from MDS and sAML patients. The screening conditions were: |logFC| \u0026gt; 1, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The results identified 1173 lncRNAs (of which 648 were up-regulated and 525 were down-regulated) and 326 mRNAs (of which 125 were up-regulated and 201 were down-regulated) that were significantly altered in sAML compared to the MDS group. The following is the volcano map and clustering heat map of the differential genes obtained from sequencing (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eIn order to study the functions of these differential genes, GO and KEGG enrichment analysis of differential genes was performed. Gene Ontology (GO) is an international standard classification system of gene function. GO can be divided into three parts: molecular function (MF), biological process (BP) and cellular component (CC). GO enrichment was characterized by p value less than 0.05. Biological processes mainly include cell metabolism, organic ring compound metabolism, compound metabolism containing nuclear bases, nitrogen compound metabolism, etc(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB(a)). Cell components include : intracellular organelles, cytoplasm, membrane-bound organelles; the molecular functions include protein binding, ion binding, DNA binding, RNA polymerase II transcription function, and oxidoreductase activity. In organisms, different genes perform their biological functions in coordination with each other, and Pathway significant enrichment can identify the most important biochemical metabolic pathways and signal transduction pathways in which candidate target genes are involved. KEGG ( Kyoto Encyclopedia of Genes and Genomes ) is the main public database on Pathway. Pathway dominance enrichment analysis took KEGG Pathway as the unit, and applied hypergeometric test to identify the pathway that was significantly enriched in candidate target genes compared with the whole genome background. Similarly, KEGG pathway enrichment was significantly enriched with p value less than 0.05. LncRNA KEGG enrichment results showed that lncRNAs involve metabolic pathways, phagocytosis, cytochrome P450 metabolic xenobiotics, antigen processing and display, glycine / serine and threonine metabolism, glycosphingolipid biosynthesis-lactate and neolactate series, and cGMP-PKG signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB(b)).\u003c/p\u003e \u003cp\u003eThe results of mRNA GO functional enrichment showed that the biological processes involved mainly include the tissue or biological occurrence of cell components, intracellular organelles, and phosphate-containing compound metabolism. Cell components include cytoskeleton, cytoplasm, membrane-bound organelles and cell connections ; molecular function is similar to lncRNA, including protein binding, ion binding, cytoskeleton protein binding, molecular function regulation and cell adhesion molecule binding (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC(a)). mRNA KEGG enrichment results showed that mRNA involved in the pathway of amino sugar and nucleotide sugar metabolism, adhesion connection, actin cytoskeleton regulation, cancer-related pathways, focal adhesion and Rap1 signaling pathway (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC(b)).\u003c/p\u003e \u003cp\u003eLncRNAs have rich biological functions and are widely involved in various important physiological processes of organisms. They can regulate the expression of target genes at the transcriptional and post-transcriptional levels, and identify differential functional pathways generated by different treatments. There are various mechanisms by which lncRNAs regulate target genes. The most common ways of regulating target genes are co-location and co-expression target gene regulation. Co-location (co-location) means that lncRNA may have regulatory effects on nearby protein-coding genes, and the analysis is done by searching for genes within 100kb upstream and downstream of lncRNA; co-expression (co-expression) means that lncRNA acts on a distant location after transcription The mode of action of the target genes was analyzed by the expression correlation among multiple samples.Through the above analysis, we screened out multiple lncRNAs that can regulate PIM2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eExpression of PCSK1N-202 in CD34\u003csup\u003e+\u003c/sup\u003e cells from MDS patients and correlation with PIM-2\u003c/h2\u003e \u003cp\u003eTo verify the sequencing results, we detected the expression levels of LncRNA PCSK1N-202 in bone marrow CD34\u003csup\u003e+\u003c/sup\u003e cells of 40 MDS patients, 24 AML patients and 31 healthy controls by RT-PCR. The expression level of PCSK1N-202 was 11.26 (0.92,153.70) in MDS group, 135.00 (14.37,1442.00) in AML group and 0.65 (0.178,4) in healthy control group. The expression level of PCSK1N-202 in MDS and AML group was significantly higher than that in healthy control group, and that in AML group was significantly higher than that in MDS group (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). According to IPSS-R risk stratification, MDS patients were divided into group A (extremely low-risk group, low-risk group and medium-risk group) and group B (high-risk group and extremely high-risk group). The expression level of PCSK1N-202 in group B was significantly higher than that in group A (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).The expression levels of PIM2 and PCSK1N-202 RNA in CD34\u003csup\u003e+\u003c/sup\u003e cells of the same patient were detected by RT-PCR. Spearman correlation analysis was used to analyze the correlation between PIM2 and PCSK1N-202 RNA expression, and the results showed that there was a significantly positive correlation between them ( Spearman r\u0026thinsp;=\u0026thinsp;0.56, p\u0026thinsp;=\u0026thinsp;0.0165 ) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). This result suggests that lncRNA PCSK1N-202 may have a positive regulatory relationship with PIM2. To validate the regulation of lncRNA PCSK1N-202 to PIM2,the cellular localization of LncRNA PCSK1N-202 was carried out by using RNA fluorescence in situ hybridization which indicated that PCSK1N-202 is distributed in the nucleus and cytoplasm(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eDown regulation of PCSK1N-202 induced MDS cell apoptosis by PIM2/HIF-1α\u003c/h2\u003e \u003cp\u003eIn order to verify the relationship between lncRNA PCSK1N-202 and PIM2, we constructed lentiviruses (LV-PCSK1N-202-72, LV-PCSK1N-202-73, LV-PCSK1N-202-74) and empty viruses that interfere with the expression of PCSK1N-202. SKM-1 was transfected with these four lentiviruses. Through the preliminary experiment we determined the transfection conditions for MOI\u0026thinsp;=\u0026thinsp;50, HiTransG P transfection enhancer, transfection efficiency was observed after 72 hours (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B). The expression level of PCSK1N-202 was detected by RT-PCR (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC), and the results showed that all three lentiviruses could knock down PCSK1N-202.The apoptosis of SKM-1 cells transfected with lentivirus LV-PCSK1N-202-72 / 73 / 74 was detected by Annexin V / 7-AD kit. The results showed that the apoptotic cells of LV-PCSK1N-202-72 / 73 / 74 were significantly increased compared with the empty virus group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD-E). The results showed that lncRNA PCSK1N-202 regulates apoptosis.EdU kit was used to detect the proliferation of SKM-1 cells after lentivirus LV-PCSK1N-202\u0026ndash;72 / 73 / 74. The results showed that the cell proliferation of LV-PCSK1N-202\u0026ndash;72 / 73 / 74 was significantly decreased compared with that of the empty virus group ( Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF-G). The results showed that lncRNA PCSK1N-202 could up-regulate cell proliferation.Western blot was used to detect the levels of PIM2 and HIF-1α protein in the cells after lentivirus LV-PCSK1N-202\u0026ndash;72 / 73 / 74 knocked down SKM-1 PCSK1N-202. The results showed that PIM2 and HIF-1α decreased significantly after knocking down PCSK1N-202 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eH).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe clinical presentation of patients with MDS varies, and the intuitive difference between patients with low-risk MDS patients and high-risk MDS patients is the number of primitive cells in the bone marrow. In terms of cell proliferation and cell death, patients with low-risk MDS mainly show ineffective hematopoiesis due to increased cell death. Studies have shown that the causes of cell death in patients with low-risk MDS are non-inflammatory and inflammatory factors; non-inflammatory factors such as apoptosis [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], while inflammatory factors include cell scorching and necrosis[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePIM kinase is mainly regulated by various cytokines and growth factors at the transcription and translation levels, including TNF-α、IL-2(interleukin-2)、IL-3、IL-6, GM-CSF (granulocyte-macrophage colony-stimulating factor) and G-CSF (granulocyte-colony stimulating factor)[\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]。The stability and function of PIM kinase are related to the binding of heat shock protein ( Hsp ) 90[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Although the functions of these three kinases are similar, their tissue distributions are different. PIM1 and PIM2 are mainly expressed in hematopoietic cells[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], but PIM-3 is highly expressed in brain, kidney and epithelial cells[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Studies have showed that PIM2 is a downstream target of the NF-κB pathway, and there are some views that PIM2 can also act as an upstream protein to regulate the NF-κB pathway. A recent study found that there is a feedback loop between PIM2 and NF-κB signaling[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Our previous studies in leukemia cells ( K562 ), multiple myeloma cells ( RPMI-8226 ) and lung cancer cells ( A549, H1299 ) found that down-regulation of PIM2 could block the cell cycle at G0 / G1 phase by increasing the expression of P21. After knocking down the expression of PIM2, the expression level of NF-kB decreased[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], These suggested that PIM2 affected the proliferation of tumor cells by regulating the cell protein p21 and NF-kB cell signaling pathway. In myeloma cell lines, zoledronic acid synergistically inhibited the growth of myeloma cells by combining with bortezomib to suppress PIM2 expression[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], It suggested that PIM2 may be involved in regulating tumor cell proliferation by modulating the cell cycle.\u003c/p\u003e \u003cp\u003eLncRNA was first discovered in 1990, when it was thought to be largely incapable of translating proteins, but its function was not clear [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Subsequently, it was found that lncRNAs can affect cell growth and differentiation through the regulation of chromatin modifications, gene expression [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. According to the ENCODE (Encyclopedia of DNA Elements) project, it is estimated that the human genome encodes more than 28,000 different long non-coding RNAs (lncRNAs), many of which are still undiscovered and remain to be annotated[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In recent years there has been an increasing number of studies on lncRNAs, especially in the field of oncology. In hematologic tumors, some differentially expressed lncRNAs have also been identified and some of them may be used as diagnostic or prognostic indicators. With the development of high-throughput sequencing technology, the research on lncRNAs has become more and more advanced.\u003c/p\u003e \u003cp\u003eIn this study, we first analyzed the publicly accessible TCGA database and analyzed PIM2 expression levels by RNA sequencing datasets of AML as well as clinical data, and our findings suggested that elevated PIM2 expression might reduce the prognostic survival time of a subset of patients with myeloid malignancies. It has been found in our previous study that PIM2 is highly expressed in CD34\u003csup\u003e+\u003c/sup\u003e cells derived from the bone marrow of MDS patients. It may be a potential biomarker for the diagnosis of MDS. We therefore speculated that elevated PIM2 expression may also correlate with poor prognosis in MDS patients.[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition, we analyzed the lncRNA expression profiles of bone marrow CD34\u003csup\u003e+\u003c/sup\u003e cells in MDS patients and sAML patients by high-throughput sequencing technology. The results showed significant differences in lncRNA expression profiles between the two groups, and moreover, 1173 lncRNAs (of which 648 were up-regulated and 525 were down-regulated) and 326 mRNAs (of which 125 were up-regulated and 201 were down-regulated) were detected that were significantly altered in sAML compared with the MDS group. To investigate the functions of these differential genes, we performed GO and KEGG enrichment analysis of differential genes. lncRNA GO enrichment showed that: the biological processes involved in lncRNAs mainly include cellular metabolic processes, organic cyclic compound metabolic processes, nucleobase-containing compound metabolic processes, nitrogen compound metabolic processes, etc.; the cellular components include: intracellular organelle part, cytoplasmic part, membrane The molecular functions include: protein binding, ion binding, DNA binding, RNA polymerase II transcriptional function, oxidoreductase activity, etc. ncRNA KEGG enrichment results show: lncRNA involved in pathways such as metabolic pathways, phagosome, cytochrome P450 metabolism xenobiotics, antigen processing and presentation, glycine/serine and threonine metabolism, glycosphingolipid biosynthesis-lactate and neo-lactate series, and cGMP-PKG signaling pathway. mRNA GO functional enrichment results show involved in biological processes The cellular components include: cytoskeleton, cytoplasmic part, membrane-bound organelles and cell junctions, etc. The molecular function part is similar to lncRNA, including: protein binding, ion binding, cytoskeletal protein binding, molecular function regulation and cell adhesion molecule binding, etc. The mRNA KEGG enrichment results showed that the mRNA involved in pathways such as amino and nucleotide sugar metabolism, adhesion junctions, regulation of actin cytoskeleton, cancer-related pathways, focal adhesions and Rap1 signaling pathway. LncRNA KEGG enrichment results show: lncRNA involved in pathways such as metabolic pathways, phagosome, cytochrome P450 metabolism xenobiotics, antigen processing and presentation, glycine/serine and threonine metabolism, glycosphingolipid biosynthesis-lactate and neo-lactate series, and cGMP-PKG signaling pathway. mRNA GO functional enrichment results show involved in biological processes The cellular components include: cytoskeleton, cytoplasmic part, membrane-bound organelles and cell junctions, etc. The molecular function part is similar to lncRNA, including: protein binding, ion binding, cytoskeletal protein binding, molecular function regulation and cell adhesion molecule binding, etc. The mRNA KEGG enrichment results showed that the mRNA involved in pathways such as amino and nucleotide sugar metabolism, adhesion junctions, regulation of actin cytoskeleton, cancer-related pathways, focal adhesions and Rap1 signaling pathway. In order to verify this hypothesis, we knocked down lncRNA PCSK1N-202 of SKM-1 cell line by lentivirus interference technology to detect cell proliferation and apoptosis. The results showed that knocking down PCSK1N-202 could lead to decreased cell proliferation and increased apoptosis. Western blot showed that PIM2 and HIF-1α decreased significantly after knocking down PCSK1N-202. This result suggested that lncRNA PCSK1N-202 could promote the malignant proliferation of MDS CD34\u0026thinsp;+\u0026thinsp;cells and inhibit their apoptosis by up-regulating PIM2 / HIF-1α. In conclusion, lncRNAs play a role in the malignant proliferation of bone marrow hematopoietic stem cells in MDS patients. lncRNA PCSK1N-202 can promote the malignant proliferation of MDS CD34\u003csup\u003e+\u003c/sup\u003e cells and inhibit their apoptosis by up-regulating PIM2 / HIF-1α.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThrough high-throughput sequencing, we found that the differential lncRNA PCSK1N-202 of CD34\u003csup\u003e+\u003c/sup\u003e cells in sAML and MDS patients can participate in the proliferation of CD34\u003csup\u003e+\u003c/sup\u003e cells in MDS patients by regulating PIM2/HIF-1α. The expression level of PIM2 in bone marrow CD34\u003csup\u003e+\u003c/sup\u003e cells of MDS patients was significantly higher than that of healthy controls. Meanwhile, lncRNA PCSK1N-202 can regulate the proliferation of CD34\u003csup\u003e+\u003c/sup\u003e cells in the bone marrow of MDS patients through the PIM2/HIF-1α cell signaling pathway.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics Committee of Tianjin Medical University General Hospital permitted this project.\u0026nbsp;The scanned copy of the ethics document has been uploaded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRong Fu and Zhaoyun Liu designed the project and proofread the manuscript. Mengyue Tian and Yue Jia carried out the experiments, Yixuan Guo analysed the data and finished the manuscript. Nanhao Meng and Lixiang Duan participated in the experimental work. All authors checked and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFundings\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China Youth Project (grant no. 81900131), the Tianjin Municipal Natural Science Foundation (grant no. 18JCQNJC80400), the Tianjin Education Commission Research Project (grant no. 2018KJ043), the Tianjin Education Commission Research Project (grant no. 2018KJ045), and the Tianjin Science and Technology Planning Project (no. 20YFZCSY00060).Tianjin Municipal Health Commission Youth Project（grant no. TJWJ2021QN001)；Medjaden Academy \u0026amp; Research Foundation for Young Scientists (Grant No. MJR20221011);Tianjin Key Medical Discipline(Specialty) Construction project.\u003c/p\u003e\n\u003cp\u003eIn addition, some of the contents of this manuscript have been published by the type of E-Poster Presentation on EHA, the author is Liu Zhaoyun, Tian Mengyue, Fu Rong (Correspondence author). click the following link for more details: https://library.ehaweb.org/eha/2021/eha2021-virtual-congress/325653/zhaoyun.liu.lncrna.pcsk1n-202.promotes.cd342Bcell.proliferation.via.pim2.hif-1.html?f=.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN/A.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAd\u0026egrave;s L, Itzykson R, Fenaux P. Myelodysplastic syndromes[J]. 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Genetic epidemiology, 2014;38(4):275\u0026ndash;280.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Myelodysplastic syndromes, CD34+ cell, PIM2, LncRNA, lncRNA-seq, PIM2/HIF-1α","lastPublishedDoi":"10.21203/rs.3.rs-3177358/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3177358/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMyelodysplastic syndromes (MDS) are characterized by malignant clonal hematopoietic stem cells with high-risk of progression to acute myeloid leukemia (AML).\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn this study,we explore the role of PIM2/HIF-1alpha in the proliferation of CD34\u0026thinsp;+\u0026thinsp;cells in MDS patients. We investigate the profile of lncRNA derived from the bone marrow CD34\u0026thinsp;+\u0026thinsp;cells in MDS patients and AML secondary to MDS (sAML) patients. We found 1173 lncRNAs (648 upregulated/525 downregulated) and 326 mRNAs (125 upregulated/201 downregulated) significantly deregulated in sAML compared to those in MDS patients (|logFC| \u0026gt; 1, p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Of these, lncRNA PCSK1N-202 predicted as targeted-regulator to PIM2.RT-PCR showed that the level of PCSK1N-202 was upregulated in AML and MDS patients and positive related with PIM2.For further demonstrated the regulation of PCSK1N-202 to PIM2,RNA fluorescence in situ hybridization indicated that PCSK1N-202 was distributed in the nucleus and cytoplasm which as well as PIM2.For functional study, SKM-1 cell was transfected with LV- PCSK1N-202 ,which induced the decline of PIM2 and HIF-1α followed with decreased of cell proliferation and increased of apoptosis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn conclusion, the upregulation of PCSK1N-202 transcript may through PIM2 / HIF-1α regulate the proliferation of CD34\u0026thinsp;+\u0026thinsp;cells in MDS.\u003c/p\u003e","manuscriptTitle":"LncRNA PCSK1N-202 regulates CD34 + hematopoietic cells proliferation in MDS patients via PIM2/HIF-1alpha","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-07-31 13:58:33","doi":"10.21203/rs.3.rs-3177358/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0e52fd77-485a-48dc-b56d-ae6d83e9b626","owner":[],"postedDate":"July 31st, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-08-17T03:44:09+00:00","versionOfRecord":[],"versionCreatedAt":"2023-07-31 13:58:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3177358","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3177358","identity":"rs-3177358","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}