Expression profiling analysis reveals molecular mechanism of Lnc00675 downregulation promoting cell apoptosis in acute myeloid leukemia U937 cells
Original Article

Expression profiling analysis reveals molecular mechanism of Lnc00675 downregulation promoting cell apoptosis in acute myeloid leukemia U937 cells

Miao Miao, Mengqi Li, Zhuogang Liu, Wei Yang, Chen Wang, Rong Hu

Department of Hematology, Shengjing Hospital, China Medical University, Shenyang, China

Contributions: (I) Conception and design: M Miao, R Hu; (II) Administrative support: R Hu; (III) Provision of study materials or patients: Z Liu, W Yang; (IV) Collection and assembly of data: M Li, C Wang; (V) Data analysis and interpretation: M Miao; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Dr. Rong Hu. Department of Hematology, Shengjing Hospital, China Medical University, 39 Huaxiang Road, Shenyang, Liaoning 110021, China. Email: hur@sj-hospital.org.

Background: Acute myeloid leukemia (AML), an aggressive malignancy with poor prognosis, is the most common in adult leukemia. Long non-coding RNA (lncRNA) could affect the regulation of protein-coding genes, cell proliferation and apoptosis, tumor cell resistance to radio- and chemotherapy and pathological processes. Lnc00675 is a lncRNA also known as transmembrane protein 238 like (TMEM238L), which identified as a marker of tumor promoter and unfavorable prognosis in patients with pancreatic ductal adenocarcinoma, glioma and cervical cancer. However, the association between Lnc00675 and hematological tumors has not been previously reported.

Methods: Expression profile gene chip technology was used to screen for differentially expressed genes (DEGs) through comparing Lnc00675 overexpression and Lnc00675 downregulation. Gene ontology (GO) analysis was performed to identify the biologic implications of the DEGs. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed to identify biologically important pathways associated with the DEGs. Cell Counting Kit-8 (CCK-8) assay and flow cytometric analysis were utilized to detect the cell proliferation rate and the cell apoptosis rate, respectively.

Results: Comparing Lnc00675 overexpression and Lnc00675 downregulation, a total of 866 and 1,115 DEGs were upregulated and downregulated, respectively. Bioinformatics analysis indicated that Lnc00675 might affect U937 cells proliferation and apoptosis through JAK-STAT signaling pathway and PI3K-Akt signaling pathway. The cell proliferation rate in si-Lnc00675 group was significantly lower than those of si-NC group and Lnc00675 group (P<0.05). The cell apoptosis rate of si-Lnc00675 group (22.93%±2.24%) was significantly higher than those of si-NC group (0.37%±0.88%) and Lnc00675 group (0.73%±0.35%) (P<0.01).

Conclusions: Downregulation of lnc00675 expression inhibited proliferation and promoted apoptosis in human leukemia U937 cells.

Keywords: Lnc00675; U937 cells; acute myeloid leukemia (AML); JAK-STAT signaling pathway; PI3K-Akt signaling pathway; expression profile analysis

Submitted Mar 28, 2020. Accepted for publication Sep 26, 2020.

doi: 10.21037/tcr-20-1714

Introduction

Acute myeloid leukemia (AML), an aggressive malignancy with poor prognosis, is the most common in adult leukemia. The therapeutic efficacy of patients with AML remains poor, with only 40% young patients (<60 years old) or 10% patients (>60 years old) achieving long-term survival (1). The pathological mechanism of AML is a series of events including changes in cell proliferation, differentiation, and apoptosis caused by pathogenic factors, such as somatic mutations, cytogenetic abnormalities, epigenetic changes (2,3).

Long non-coding RNAs (lncRNAs) are e a class of RNAs longer than 200 nucleotides, which don’t have the function of encoding proteins (4). LncRNA could affect protein-coding gene regulation, cell proliferation and apoptosis, tumor cell resistance to radio- and chemotherapy and pathological processes by participating in transcriptional regulation and post-transcriptional regulation (5-8). Accumulating evidence supports that misregulation of lncRNA-based epigenetic networks contribute to many types of cancer (9,10). Lnc00675 is a lncRNA also known as transmembrane protein 238 like (TMEM238L), and is identified as a marker of tumor promoter and unfavorable prognosis in patients with pancreatic ductal adenocarcinoma (11), glioma (12) and cervical cancer (13). In spite of the aforementioned link between Lnc00675 and cancer, very few researches have been carried out to find the molecular mechanism of Lnc00675 in cancer metastasis. Li et al. reported the positively correlation between Lnc00675 expression and TRIP6 protein expression in glioma tissues and cell lines (12). Ma et al. reported that LINC00675 promoted cervical tumorigenesis by modulating the Wnt/β-catenin pathway (13).

However, the association between Lnc00675 and hematological tumors has not been previously reported. In the current study, we analyzed the effect of Lnc00675 on proliferation and apoptosis in human leukemia U937 cells, and the other aim of the current study was to investigate molecular mechanism of Lnc00675 using expression profiling analysis. Our results probably identify Lnc00675 as a novel therapeutic target and provide a new perspective for molecular mechanisms of AML.

Methods

Cell culture and transfection

Human leukemia U937 cells (RRID: CVCL_0007) was cultured in 90% RPMI-1640 (Hyclone, USA) + 10% FBS (Gibco, USA) + penicillin (100 U/mL) and streptomycin (100 g/mL). Cells were cultured under 5% CO2 and 95% air in an incubator set at 37 °C. U937 cells in logarithmic growth phase were divided into three groups, such as Lnc00675 group, si-Lnc00675 group and si-NC group. U937 cells were seeded in 25 cm2 cell culture flasks.

Cell transfection

Transfections were performed using LipofectamineTM 2000 (Invitrogen, USA). U937 cells suspended in serum-free RPMI-1640 were inoculated in 25 cm2 cell culture flasks to undergo transfection with Lnc00675 overexpression vector (Lnc00675 group), Lnc00675 siRNA vector (si-Lnc00675 group), and Lnc00675 siRNA negative control vector (si-NC group), respectively. All nucleotide vectors were purchased from Shanghai Genechem Co., Ltd. (China).

Microarray analysis

U937 cells of Lnc00675 group and si-Lnc00675 were isolated, pelleted cells by centrifugation, respectively. Used 1 mL of TRIzol Reagent (Invitrogen, USA) to lyse 1×107 U937 cells by repetitive pipetting. Microarray experiments were conducted by Shanghai KangChen Biotech (China) with Agilent Human 4x44K Gene Expression Microarray chips with 444,000 probes, the Agilent One-Color Microarray-Based Gene Expression Analysis protocol was used, including total RNA Clean-up and RNA QC, purify the labeled/amplified RNA and labeled cRNA QC, hybridization, microarray Wash, Scanning, extract data using Agilent Feature Extraction software. Bioconductor DESeq2 version 1.12.3 (https://www.rdocumentation.org/packages/DESeq2) was used to identify differentially expressed genes (DEGs) using a fold change (FC) >2 for significant upregulation or significant downregulation and a false discovery rate (FDR) <0.05. A scatter plot was drawn according to the analysis of the DEGs. Gene ontology (GO, www.geneontology.org) analysis was performed to identify the biologic implications of the DEGs. Fisher’s exact test was used to identify the significant GO terms with FDR-adjusted P values. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed to identify biologically important pathways associated with the DEGs. Fisher’s exact test was used to select the significant pathways based on P values (P<0.05) and FDR (FDR <0.27).

Cell apoptosis detection by flow cytometry

The cells of Lnc00675 group, si-Lnc00675 group and si-NC group were seeded in 6-well cell culture plate, respectively. After 48 h of transfection, the U937 cells were washed with PBS. Flow cytometry was used to detect the apoptosis rates of the three groups. The staining was performed by Annexin V-FITC/PI double staining method (GenStar, China). Binding buffer was used to resuspend cells, 5 µL of Annexin V-FITC was added, then incubated at room temperature for 15 minutes in the dark. PI staining (5 µL) was added for 5 minutes before detection. A FACS Calibur cell analyzer (BD Biosciences) was used to analyze cell apoptosis and apoptosis rate. The percentages of apoptotic cells including early apoptotic cells (Annexin V+/PI− cells) and late stage apoptotic cells (Annexin V+/PI+ cells) were calculated.

Cell Counting Kit-8 (CCK-8) assay

The viability of U937 cells was detected using CCK-8 assay (Coffit, China). U937 cells (1×105 cells/mL) in the logarithmic growth phase were prepared as cell suspensions using RPMI-1640 containing 10% FBS. Cell suspension (100 µL) was inoculated into a well of 96-well plates. 96-well plate was incubated at 37 °C and 5% CO2 for 24, 48 or 72 h after transfection. CCK-8 solution (10 µL) was added to each well and incubated for 2 h at 37 °C. The absorbance of each well was measured by microplate reader (Shanghai Flash Spectrum Biotechnology, China) at a wavelength of 450 nm. The proliferation rate was calculated using the equation: proliferation rate (%) = (ODtreatment − ODblank)/(ODcontrol − ODblank) ×100%.

Statistical analysis

GO and KEGG analyses were performed using the online database DAVID 6.8 (https://david.ncifcrf.gov/). The difference between 2 groups was determined by unpaired Student’s t‐test using GraphPad prism 8.0 software. The differences were considered statistically significant at P<0.05. All experimental results are presented as the mean ± SD.

Results

Differential gene expression

By comparing Lnc00675 group with si-Lnc00675 group, the microarray analysis determined a total of 1,981 DEGs (FC ≥2) (Figure 1): 866 genes were upregulated and the remaining 1,115 genes were downregulated. Tables 1,2 showed the TOP50 upregulated genes and the TOP50 downregulated genes, respectively.

Figure 1 Scatter plot of upregulated and downregulated differentially expressed genes comparing between Lnc00675 group and si-Lnc00675.

Table 1

The TOP50 upregulated genes (Lnc00675 vs. si-Lnc00675)

NO. Gene symbol Description Probe Name GenBank accession Fold change
1 CCIN Calicin A_23_P60227 NM_005893 1,964.76
2 LOC100129931 Uncharacterized LOC100129931 A_33_P3277883 NR_033828 1,235.66
3 CCDC64B Coiled-coil domain containing 64B A_33_P3335590 NM_001103175 161.49
4 CEP104 Centrosomal protein 104 kDa A_33_P3405754 BC050721 59.59
5 RAB7A Member RAS oncogene family A_33_P3226492 AF119891 51.25
6 SFN Stratifin A_33_P3389286 NM_006142 51.13
7 UTP18 UTP18 small subunit processome component A_23_P130020 NM_016001 42.96
8 LINC01123 Long intergenic non-protein coding RNA 1123 A_33_P3228609 NR_046110 42.82
9 LINC01061 Long intergenic non-protein coding RNA 1061 A_24_P691775 NR_037596 42.68
10 KRTAP1-4 Keratin associated protein 1-4 A_33_P3213006 NM_001257305 42.59
11 FAM178B Family with sequence similarity 178 member B A_33_P3287119 NM_001122646 34.59
12 EFTUD1 Elongation factor Tu GTP binding domain containing 1 A_24_P754817 NM_024580 33.30
13 MAGIX MAGI family member, X-linked A_24_P66105 NM_024859 31.73
14 DHRS4L1 Dehydrogenase/reductase SDR family member 4 like 1 A_33_P3359368 NM_001277864 29.70
15 SHISA5 Shisa family member 5 A_33_P3270636 NM_001272068 29.61
16 SLC51B Solute carrier family 51, beta subunit A_23_P436284 NM_178859 28.48
17 TBC1D31 TBC1 domain family, member 31 A_23_P334218 NM_145647 28.18
18 PPP1R14A Protein phosphatase 1, regulatory (inhibitor) subunit 14A A_33_P3401647 NM_033256 27.34
19 JAKMIP2 Janus kinase and microtubule interacting protein 2 A_33_P3255290 NM_014790 26.58
20 RAP1GAP2 RAP1 GTPase activating protein 2 A_24_P36890 NM_002885 26.24
21 OR52E8 Olfactory receptor, family 52, subfamily E, member 8 A_33_P3281990 NM_001005168 25.55
22 SSPO SCO-Spondin A_33_P3277178 AK093431 25.43
23 PPP1R1A Protein phosphatase 1, regulatory (inhibitor) subunit 1A A_33_P3383471 AK123969 25.30
24 MAGEB6 Melanoma antigen family B, 6 A_33_P3368755 NM_173523 24.11
25 BCR Breakpoint cluster region A_24_P127235 NM_004327 24.05
26 DCLRE1B DNA cross-link repair 1B A_24_P54131 NM_022836 23.81
27 RNF150 Ring finger protein 150 A_24_P350589 NM_020724 23.74
28 HERC6 HECT and RLD domain containing E3 ubiquitin protein ligase family member 6 A_33_P3315779 NM_001165136 23.19
29 CUL4A Cullin 4A A_33_P3322909 NM_001278513 23.00
30 SCOC-AS1 SCOC antisense RNA 1 A_24_P145019 NR_033939 22.94
31 ATXN3L Ataxin 3-like A_23_P361744 NM_001135995 22.73
32 BTN3A1 Butyrophilin, subfamily 3, member A1 A_33_P3388466 NM_007048 22.47
33 AKAP12 A kinase (PRKA) anchor protein 12 A_23_P111311 NM_144497 21.77
34 CDCA7 Cell division cycle associated 7 A_33_P3296169 NM_031942 21.75
35 ZDHHC3 Zinc finger, DHHC-type containing 3 A_33_P3327479 NM_016598 21.66
36 STARD13 StAR-related lipid transfer (START) domain containing 13 A_23_P342727 NM_178006 21.51
37 CTNND1 Catenin, delta 1 A_33_P3209716 NM_001206885 21.20
38 PPAN-P2RY11 PPAN-P2RY11 readthrough A_33_P3239759 NM_001198690 21.06
39 REP15 RAB15 effector protein A_33_P3247624 NM_001029874 20.87
40 MECP2 Methyl CpG binding protein 2 A_33_P3339036 NM_001110792 20.70
41 PIK3R5 Phosphoinositide-3-kinase, regulatory subunit 5 A_23_P66543 NM_014308 20.65
42 THOC2 THO complex 2 A_33_P3235690 NM_001081550 20.63
43 ZCCHC13 Zinc finger, CCHC domain containing 13 A_32_P11096 NM_203303 20.20
44 EGFR Epidermal growth factor receptor A_33_P3351944 NM_201283 20.01
45 FBXO2 F-box protein 2 A_23_P45999 NM_012168 19.78
46 BICC1 Bicc family RNA binding protein 1 A_33_P3293913 NM_001080512 19.61
47 PCM1 Pericentriolar material 1 A_24_P555510 NM_006197 19.56
48 SPECC1L Sperm antigen with calponin homology and coiled-coil domains 1-like A_33_P3214027 NM_001254732 19.26
49 RIMS3 Regulating synaptic membrane exocytosis 3 A_23_P319583 NM_014747 19.16
50 TRHDE-AS1 TRHDE antisense RNA 1 A_33_P3311493 NR_026836 19.03

Table 2

The TOP50 downregulated genes (Lnc00675 vs. si-Lnc00675)

NO. Gene symbol Description Probe name GenBank accession Fold change
1 DBF4B DBF4 zinc finger B A_24_P253780 NM_145663 910.03
2 KAT2B K(lysine) acetyltransferase 2B A_32_P159651 NM_003884 426.94
3 FAM50B Family with sequence similarity 50, member B A_23_P8240 NM_012135 214.33
4 CPSF4L Cleavage and polyadenylation specific factor 4-like A_33_P3265194 – 135.99
5 LOC651337 Uncharacterized LOC651337 A_33_P3617190 AK124119 69.68
6 NOC3L Nucleolar complex associated 3 homolog A_23_P202496 NM_022451 56.46
7 MED23 Mediator complex subunit 23 A_23_P330999 NM_015979 55.58
8 DPH2 DPH2 homolog A_24_P393844 NM_001384 47.56
9 FOXN2 Forkhead box N2 A_32_P140898 NM_002158 28.38
10 SLCO3A1 Solute carrier organic anion transporter family, member 3A1 A_24_P336276 NM_013272 26.61
11 TMEM63A Transmembrane protein 63A A_23_P200489 NM_014698 25.86
12 RBM5 RNA binding motif protein 5 A_23_P18276 NM_005778 25.57
13 MAP4 Microtubule-associated protein 4 A_23_P211814 NM_002375 22.55
14 IRF3 Interferon regulatory factor 3 A_23_P27677 NM_001571 18.69
15 SUGCT Succinyl-CoA:glutarate-CoA transferase A_23_P145711 NM_024728 15.75
16 IQSEC2 IQ motif and Sec7 domain 2 A_23_P330788 NM_015075 15.01
17 ELMOD3 ELMO/CED-12 domain containing 3 A_33_P3297302 NM_001135021 14.54
18 MEF2BNB MEF2B neighbor A_33_P3354771 AK057161 14.32
19 UNC80 Unc-80 homolog A_33_P3410251 AK090815 14.23
20 LRRC8C Leucine rich repeat containing 8 family, member C A_33_P3406030 NM_032270 14.13
21 ELF4 E74-like factor 4 A_24_P340066 NM_001421 13.86
22 METTL20 Methyltransferase like 20 A_33_P3318966 NM_173802 12.63
23 C2CD4C C2 calcium-dependent domain containing 4C A_33_P3215412 NM_001136263 12.40
24 ZBTB7C zinc finger and BTB domain containing 7C A_33_P3402304 NM_001039360 12.04
25 NEUROD2 Neuronal differentiation 2 A_32_P25295 NM_006160 11.83
26 RASD3 RASD family member 3 A_33_P3349912 NM_001257357 10.53
27 PCDHGC4 Protocadherin gamma subfamily C, 4 A_23_P303101 NM_032406 10.50
28 TMEM254 Transmembrane protein 254 A_23_P97853 NM_025125 10.23
29 ANK2 Ankyrin 2 A_33_P3287967 NM_001148 9.69
30 LOC101928000 Uncharacterized LOC101928000 A_33_P3258712 XR_243583 9.43
31 SLC31A1 Solute carrier family 31, member 1 A_24_P321068 NM_001859 9.39
32 LOC100133985 Uncharacterized LOC100133985 A_33_P3422654 NR_024444 9.36
33 LINC01349 Long intergenic non-protein coding RNA 1349 A_33_P3300067 NR_038914 9.27
34 CHERP Calcium homeostasis endoplasmic reticulum protein A_23_P16139 NM_006387 9.26
35 SPRR2C Small proline-rich protein 2C A_23_P126089 NR_003062 9.12
36 NDRG1 N-myc downstream regulated 1 A_23_P20494 NM_006096 9.11
37 SLC9A4 Solute carrier family 9, subfamily A, member 4 A_33_P3396270 NM_001011552 9.06
38 GSTM2P1 Glutathione S-transferase mu 2 pseudogene 1 A_23_P58869 NR_002932 8.68
39 OR2A2 Olfactory receptor, family 2, subfamily A, member 2 A_33_P3394312 NM_001005480 8.68
40 PFKFB3 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 A_24_P206604 NM_004566 8.47
41 TPSAB1 Tryptase alpha/beta 1 A_23_P37702 NM_003294 7.97
42 KIF2C Kinesin family member 2C A_23_P34788 NM_006845 7.88
43 SLC6A8 Solute carrier family 6, member 8 A_23_P159937 NM_005629 7.74
44 ITGA11 Integrin, alpha 11 A_33_P3353791 NM_181501 7.58
45 ANXA2R Annexin A2 receptor A_33_P3299279 NM_001014279 7.49
46 GINS1 GINS complex subunit 1 A_33_P3340025 NM_021067 7.49
47 LOC283887 Uncharacterized LOC283887 A_33_P3677061 XR_132607 7.39
48 FAM178A Family with sequence similarity 178, member A A_23_P356139 NM_018121 7.24
49 CLEC12B C-type lectin domain family 12, member B A_33_P3303519 NM_205852 7.11
50 GCRG224 Gastric cancer-related gene GCRG224 A_33_P3398867 AF438406 7.09

GO analysis of the DEGs

GO analysis contained three domains that represent gene function based on cellular component, biological process and molecular function. A total of 1,385 DEGs were associated with the cell composition domain, of which 608 were upregulated (Figure 2A) and 777 genes were downregulated (Figure 2B). The TOP5 enrichment score biological process terms were “non-membrane-bounded organelle”, “intracellular non-membrane-bounded organelle”, “cytoplasmic vesicle”, “intracellular vesicle” and “cytoplasmic part”. A total of 1,320 DEGs were associated with the biological process domain, of which 581 were upregulated (Figure 3A) and 739 were down-regulated (Figure 3B). The TOP5 enrichment score biological process terms were “oxoacid metabolic process”, “oxidation-reduction process”, “organic acid metabolic process”, “carboxylic acid metabolic process” and “small molecule metabolic process”. A total of 1,324 DEGs were associated with the molecular function domain, of which 580 were upregulated (Figure 4A) and 744 were down-regulated (Figure 4B). The five most enriched molecular function terms were “oxidoreductase activity”, “protein binding”, “steroid dehydrogenase activity, acting on the CH-OH group of donors, NAD or NADP as acceptor”, “protein binding” and “oxidoreductase activity, acting on paired donors, with incorporation or reduction of molecular oxygen”.

Figure 2 Gene ontology cellular component classification. (A) Cellular component classification of upregulated differentially expressed genes; (B) cellular component classification of downregulated differentially expressed genes.
Figure 3 Gene ontology biological process classification. (A) Biological process classification of upregulated differentially expressed genes; (B) biological process classification of downregulated differentially expressed genes.
Figure 4 Gene ontology molecular function classification. (A) Molecular function classification of upregulated differentially expressed genes; (B) molecular function classification of downregulated differentially expressed genes.

Pathway analysis of the DEGs

Pathway analysis of the DEGs allows the identification of DEGs related to specific cell pathways. Pathway analysis revealed that DEGs were significantly enriched in 73 pathways (Figure 5A,B). The upregulated genes were involved in 23 pathways and the downregulated DEGs were involved in 50 pathways. The upregulated DEGs were mainly involved in “JAK-STAT signaling pathway”, “Cell cycle”, “Amoebiasis”, “Necroptosis”, “Nucleotide excision repair”, “Inflammatory bowel disease (IBD)”, “Adrenergic signaling in cardiomyocytes”, “ErbB signaling pathway”, “PI3K-Akt signaling pathway” and “Renal cell carcinoma”. The downregulated DEGs were mainly involved in “Steroid biosynthesis”, “Glycosaminoglycan degradation”, “Adherens junction”, “Lysosome, Ferroptosis”, “HIF-1 signaling pathway”, “Central carbon metabolism in cancer”, “Carbon metabolism”, “Glycolysis/Gluconeogenesis”, “Amino sugar and nucleotide sugar metabolism” and “Fatty acid metabolism”.

Figure 5 Significantly enrichment pathway analysis of differentially expressed (DE) genes. (A) Upregulated DE genes involved in the Top10 pathways; (B) downregulated DE genes involved in the Top10 pathways.

Effects of Lnc00675 on proliferation and apoptosis in U937 cells

The proliferation rate of si-Lnc00675 group was significantly lower than those of si-NC group and Lnc00675 group at all three time points (P<0.05). There was no significant difference in proliferation rate between si-NC group and Lnc00675 group (P>0.05) (Figure 6A). Flow cytometric analysis indicated that the downregulation of Lnc00675 significantly promoted cell apoptosis. The cell apoptosis rate of si-Lnc00675 group (22.93±2.24) was significantly higher than those of si-NC group (0.37±0.88) and Lnc00675 group (0.73±0.35) (P>0.01) (Figure 6B).

Figure 6 Downregulation of Lnc00675 expression inhibited proliferation and induced cell apoptosis in U937 cells. (A) Cell proliferation was measured by CCK8 assay in U937 cells of Lnc00675 group, si-Lnc00675 group and si-NC group; (B) flow cytometry assay was performed to examine cell apoptosis in U937 of Lnc00675 group, si-Lnc00675 group and si-NC group. *, P<0.05 between si-Lnc00675 group and si-NC group or Lnc00675 group.

Discussion

With the increasing understanding of the lncRNA, the association between tumorigenesis and lncRNA has attracted more and more attention. Notably, Multiple AML researches had shown that the high expression of lncRNA could lead to promote cell proliferation, repress apoptosis, worse prognosis and poor treatment outcomes, such as ZEB2-AS1 (14), lnc-SOX6-1 (15), lnc-CRNDE (16), lnc-HOTAIR (17). With regard to glioma, the high expression of Lnc00675 was dramatically associated with large tumor and advanced World Health Organization grade size (12). The high expression of Lnc00675 positively correlated with poor survival, perineural invasion and lymph node metastasis in patients with pancreatic ductal adenocarcinoma (11). But there is currently no research results available for correlation between Lnc00675 and AML. In the present study, we first reported that the downregulation of Lnc00675 expression resulted in inhibiting cell proliferation and inducing cell apoptosis in U937 cells, but overexpression of Lnc00675 had no effect on the proliferation and apoptosis in U937 cells.

The Wingless (Wnt)/β-catenin signaling pathway has been associated with metabolic reprogramming of cancer cells, cancer stem cells, tumorigenesis and tumor plasticity (18). Ma et al. reported that Lnc00675 inhibited apoptosis and promoted proliferation, migration and invasion though the Wnt/β-catenin pathway in cervical cancer cells, and lithium chloride could attenuate the effects of Lnc00675 knockdown (13). Shan et al. revealed that Lnc00675 downregulated miR-942 expression in colorectal cancer cells, and miR-942 bound to 3’UTR of glycogen synthase kinase-3β (GSK-3β, a kinase mediating β-catenin phosphorylation in Wnt/β-catenin pathway) by dual-luciferase reporter assay (19). At present, there are no studies investigating the molecular mechanism of Lnc00675 in AML cells. In this regard, KEGG pathway analysis were performed using standard enrichment calculation methods to reveal the molecular mechanism. The result of pathway analysis indicated that Lnc00675 involved in JAK-STAT signaling pathway and PI3K-Akt signaling pathway. The activation of JAK-STAT signaling pathway was implicated in the pathogenesis of AML (20,21), and targeting of this pathway was an effective therapeutic strategy for AML (22,23). Dos Santos et al. demonstrated that the PI3K-Akt signaling pathway was constitutively activated in approximately 60% of AML patients cells (24). PI3K-Akt signaling pathway inhibitors, which used alone or with other drugs, have been proven effective for suppressing cell proliferation and promoting apoptosis in AML patients, cell lines or animal models (25).

Epidermal growth factor receptor (EGFR) and interleukin 2 receptor subunit alpha (IL2RA) are involved in both JAK-STAT signaling pathway and PI3K-Akt signaling pathway. Comparing upregulation of Lnc00675 with downregulation of Lnc00675, we found that the expressions of EGFR (FC =20.01) and IL2RA (FC =10.56) were drastically upregulated. EGFR is a cell membrane receptor tyrosine kinase, and mutant EGFR are meaningful serological markers for diagnosis of AML (26). EGFR small molecule inhibitors have been reported to induce complete and durable remission in AML patients (27). Researches indicated a strong association of IL2RA expression with tyrosine kinases pathways. Upregulation of IL2RA expression was correlated with upregulation expressions of fms related receptor tyrosine kinase 3 (FLT3) (28) and inhibitor of DNA binding 1 (ID1) (29), a key target of tyrosine kinases contributing to leukemia transformation. High expression of IL2RA mRNA was an independent and adverse prognostic factor in AML (30).

The present study, to best of our knowledge, was the first to reveal that downregulation of Lnc00675 expression inhibited proliferation and promoted apoptosis in human leukemia U937 cells. By comparing upregulation of Lnc00675 and downregulation of Lnc00675. We identified 866 upregulated DEGs and 1,115 downregulated DEGs, and indicated that Lnc00675 probably affected U937 cells proliferation and apoptosis through JAK-STAT signaling pathway and PI3K-Akt signaling pathway. We will elucidate molecular mechanism of Lnc00675 in AML and further validate the Lnc00675-mediated signaling pathways in our following researches. The results obtained in the current study may aid in the elucidation of molecular mechanisms of Lnc00675 in AML and contribute to the development of target therapies to treat AML.

Acknowledgments

Funding: The present study was supported by grants from the Scientific Research Project of Education Department of Liaoning Province (grant no. JC2019011).

Footnote

Data Sharing Statement: Available at http://dx.doi.org/10.21037/tcr-20-1714

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/tcr-20-1714). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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Cite this article as: Miao M, Li M, Liu Z, Yang W, Wang C, Hu R. Expression profiling analysis reveals molecular mechanism of Lnc00675 downregulation promoting cell apoptosis in acute myeloid leukemia U937 cells. Transl Cancer Res 2020;9(11):6867-6880. doi: 10.21037/tcr-20-1714

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