{"paper_id":"07c6bf99-d9a2-4e7c-81e5-1ee32dfdd5e7","body_text":"Acute myeloid leukemia (AML) is a genetically and clinically heterogeneous hematologic malignancy [ 1 ] with a 3.7/100 000 incidence per year [ 2 ]. Nearly 80% of adult acute leukemia are AML [ 3 ], and the 5-year overall survival rate for AML patients older than 60 years is about 25% [ 4 ]. The application of various first-line chemotherapeutic agents, molecular-targeted agents, immunotherapeutic agents and hematopoietic stem cell transplantation (HSCT) has dramatically improved the treatment outcomes of AML patients [ 5 ,  6 ]. However, the relapse rate of AML patients is 80% [ 7 ], and the mortality rate has been over 50% [ 8 ]. Stratified diagnosis and treatment of AML have become the focus of research in recent years. The classification of AML is based on cytogenetic and mutational profiles. Moreover, some additional pre-disposing features are considered as prognostic factors, which include therapy-related, prior myelodysplastic syndrome (MDS) or MDS/myeloproliferative neoplasm [MPN], and germline predisposition [ 9 ]. Also, the response to initial therapy and assessment of early minimal residual disease (MRD) is also crucial in risk classification[ 9 ]. Based on the existing risk-stratification system, patients in different risk strata accept the corresponding treatment. Even so, there is still a chance of drug resistance and relapse in low- and intermediate-risk patients.\nKaryotyping is crucial in the risk stratification of AML. It was reported that 40–50% AML patients have a normal karyotype (NK) [ 10 ]. Single genes, such as  CEBPA  [ 11 ],  FLT3-ITD  [ 12 ,  13 ] and  NPM1  [ 13 ], could provide references for predicting the prognosis of NK-AML patients. It used to be considered that patients with NK-AML had a medium prognosis. However, it was found that NK-AML patients with high-risk mutated genes or aberrantly expressed genes had poor prognosis [ 14 ,  15 ]. This situation suggested that the risk stratification of NK-AML patients required further improvements. Gene expression-based scoring systems have potentials in predicting the prognostic value in AML [ 16 ]. Therefore, novel prognostic biomarkers are highly anticipated to improve the risk stratification for NK-AML.\nBased on the ImmuCo database and clinical specimens, we screened seven genes associated with acute leukemia as candidate prognosis biomarkers. In the follow-up verification, we found that the expression level of Small Integral Membrane Protein 3 ( SMIM3 , also called Nid67 )  in AML was significantly higher than that in normal controls. SMIM families contain multiple members. Small integral membrane protein 1 ( SMIM1 ), a tail-anchored transmembrane protein [ 17 ], is associated with Vel-negative blood type [ 18 ,  19 ].  SMIM1  also could influence red blood cell traits [ 20 ]. A study revealed that  SMIM4  is a respiratory chain assembly factor [ 21 ].  SMIM20  is expressed in the adult brain, and may function in fertility and reproduction [ 22 ]. A study suggested that  SMIM20  could be a new target of endometriosis [ 23 ]. Sha Liu et al. found that  Lnc-SMIM20- 1 upregulation is associated with poor prognosis in AML [ 24 ]. In addition,  SMIM30  could promote the progression of hepatocellular carcinoma [ 25 ,  26 ].\nThe  SMIM3  gene is located on chromosome 5q33.1, coding a single-pass transmembrane protein consisting of 60 amino acids with a total molecular weight of 6593 Da. It is expressed in various tissues, with the highest expression in heart, ovarian and adrenal glands, and the lowest expression in skeletal muscle and cerebellum [ 27 ]. It may play a role in cell channel regulation and be associated with neuronal differentiation [ 27 ]. There are few studies on  SMIM3 , and certainly not have been studied in AML. Thus, large gaps remain to be filled in our understanding of the function and mechanism of  SMIM3  in AML .  Currently,  SMIM3 -related hematological disease is 5q- syndrome of MDS. A study showed that a gene or genes in the Cd74 to Nid67 interval might be associated with MDS [ 28 ]. However, the mechanism has not been studied in details. In addition,  SMIM3  can be used as a sensitive and specific biomarker of radiation exposure in the radiation emergency department, and patients with expression of  SMIM3  had a poor prognosis [ 29 ]. Weining Wang et al. found that eleven genes including  SMIM3  in NCCS (n = 36) and TCGA (n = 40) databases were associated with poor overall survival rate in oral squamous cell carcinoma patients without nodal metastases [ 30 ]. However, more evidence is needed to prove whether  SMIM3  is a prognostic biomarker in oral squamous cell carcinoma.\nIn this study, we examined the expression and prognostic value of  SMIM3  in AML. We further demonstrated the effect of  SMIM3  on cellular and biological behavior both in vitro and in vivo. Meanwhile, we investigated the mechanism of  SMIM3  regulation. We also correlated the  SMIM3  expression with targeted therapy responsiveness.\n\nWe collected and compared the  SMIM3  expression data of 264 hematopoietic stem cell (HSC) samples and 814 AML bone marrow mononuclear cells (BMMC) in the ImmuCo database[ 31 ] ( http://immuco.bjmu.edu.cn ). Also, 8295 normal samples and 9807 tumor samples in UCSC XENA ( https://xena.ucsc.edu ), Genotype-Tissue Expression (GTEx) ( http://commonfund.nih.gov/GTEx/ ) and The Cancer Genome Atlas (TCGA) database ( https://tcga-data.nci.nih.gov/tcga/ ) were compared (including 173 AML samples). In the Gene Expression Omnibus (GEO) database ( http://www.ncbi.nlm.nih.gov/geo/ ),  GSE12417  - GPL97  and  GSE12417 - GPL570  [ 32 ] were used for gene expression and survival analyses.\nThe 236 bone marrow samples from newly diagnosed AML patients and 23 samples from healthy donors were enrolled at the First Affiliated Hospital of Zhengzhou University between February 2017 and March 2022. The exclusion criteria were patients who didn’t treat or treat elsewhere and patients with acute promyelocytic leukemia. The inclusion criteria was patients who accepted at least one course of treatment. We referred to this cohort as the ZZU cohort. Clinical information acquired from patient medical records mainly included gender, age, white blood cell count (WBC), hemoglobin (HGB), platelet (PLT), peripheral blasts (PB), bone marrow (BM) blasts at diagnosis, fusion gene, gene mutations and chromosomal karyotype, risk stratification, treatment regimens, transplant, and survival status. The induction therapy contained IA and DA regimens: standard-dose cytarabine (Ara-C) 100–200 mg·m − 2 ·d − 1  × 7 d combined with idarubicin 10–12 mg·m − 2 ·d − 1  × 3d or daunorubicin (DNR) 60 mg·m − 2 ·d − 1  × 3d. After remission, patients accepted high-dose Ara-C 3 g/m 2 , every 12 h × 3d. Patients without HSCT accepted four courses. Patients with HSCT accepted two courses, and then they accept HSCT. Patients over 60 years old or patients who cannot tolerate intensive chemotherapy accepted chemotherapy with demethylating drugs ± CAG ± venetoclax regimen until progression. Subjects were followed up until death, loss to follow-up or March 2022. The diagnosis of AML, complete remission (CR), relapse, risk stratification and overall survival (OS) were defined according to NCCN guideline for acute myeloid leukemia Version 2.2021[ 33 ]. The study was approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University and informed consent was obtained according to the Declaration of Helsinki.\nNext-Generation sequencing was applied to assess the mutational hotspots of genes. Based on an Illumina MiSeq System (Illumina, San Diego, CA) high-throughput sequencing platform, a Rightongene AML/MDS/MPN Sequencing Panel (Rightongene, Shanghai, China) was applied to finish the detection. Details of the variant calling, filtering, and annotation are shown in the published reports [ 34 ].\nBased on the International System for Human Cytogenetic Nomenclature, chromosomal banding analyses were performed by G-banding techniques. Real-time quantitative polymerase chain reaction (RT-qPCR) was performed to detect fusion genes with Multiplex RT-qPCR Fusion Gene Kits (Rightongene, Shanghai, China).\nThe human AML cell line Kasumi-1 was purchased from American Type Culture Collection (Manassas, VA, USA). The human AML cell line THP-1 was purchased from the cell bank of the Chinese Academy of Sciences (Shanghai, China). The cell lines were cultured in 90% Roswell Park Memorial Institute (RPMI )  1640 supplemented with 10% Fetal bovine serum (FBS) and 1% penicillin/streptomycin (P/S) (all from Gibco, Billings, MT, USA). The culture conditions were 37 °C, 5% CO 2 , and 95% humidity. SC79 (Beyotime, Shanghai, China) was used as an AKT activator.\nLentiviral shRNA transduction was performed in Kasumi-1 and THP-1 cells with human  SMIM3  shRNA lentiviral particles (Genechem, Shanghai, China) or empty control lentiviral particles (Genechem, Shanghai, China). All infections were done at a multiplicity of infection (MOI) of 100. At 12 h post-transfection, media containing lentiviral particles was replaced with fresh complete medium. Stably transfected Kasumi-1 and THP-1 cells were selected with 2 mg/ml puromycin dihydrochloride (Genechem, Shanghai, China) at 72 h post-infection. Stable  SMIM3 -knockdown cells and control cells were acquired 4 weeks after antibiotic selection. The expression level of  SMIM3  was confirmed by RT-qPCR and the immune fluorescence (IF) technique.\nBone marrow samples were collected into Ethylene Diamine Tetraacetic Acid (EDTA) anticoagulant–containing tubes. Mononuclear cells were obtained via density gradient centrifugation. Total RNA was extracted using TRIzol Reagent (Invitrogen, Carlsbad, CA, USA). The cDNA was synthesized using a High Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA) [ 35 ].  SMIM3  transcript levels were detected by the Taqman method using RT-qPCR as previously described [ 35 ]. Serial dilutions of plasmids expressing  SMIM3  and  ABL1  (Genechem, Shanghai, China) were amplified to construct standard quantification curves. The  SMIM3  and  ABL1  copy numbers were calculated from standard curves using Ct values. The  SMIM3  transcript level was calculated as the ratio of the  SMIM3  copy number/ ABL1  copy number as previously described [ 36 ].The primers and probe sequences of  SMIM3  and  ABL1  are shown in Additional file  1 : Table S1.\nThe cells in T25 flasks were collected and washed several times with phosphate-buffered saline (PBS). Then the cells were fixed using 4% paraformaldehyde (PFA) for 20 min at room temperature (RT). Further, Triton-X-100 (Beyotime, Shanghai, China) was applied to permeabilized cells for 10 min, and nonspecific binding was blocked with 5% BSA (Solaibao Biotechnology, Beijing, China) for 30 min at RT. Followed by washing, cells were incubated overnight at 4 °C with diluted (1:100) primary anti- SMIM3  Polyclonal Antibody (Thermo Fisher Scientific, Waltham, MA, USA). The cells were then incubated with diluted (1:200) secondary antibody Cy3 conjugated Goat Anti-Rabbit IgG (H + L) (Servicebio, Wuhan, China) for 1 h at RT, followed by washing in PBS and staining with DAPI (Solaibao Biotechnology, Beijing, China). Analysis was conducted under a confocal laser scan microscope (Zeiss, Oberkochen, Germany).\nRIPA lysis buffer (Beyotime, Shanghai, China) supplemented with Protein phosphatase inhibitor (Biomed, Beijing, China) and phenylmethylsulfonylfluoride (PMSF, Biomed) was used for protein extraction. Lysates were run on 10% polyacrylamide gel electrophoresis (PAGE) gels, and protein bands were transferred to 0.45 μm polyvinylidene difluoride (PVDF) membrane (Millipore, Billerica, MA, USA), then blocked with 5% skim milk at room temperature for 2 h. The membrane was incubated with primary antibodies (GAPDH, cleaved-PARP, cleaved caspase3, p27 Kip1, Cyclin D1, CDK4, p-AKT, AKT, PI3K, Cell Signaling Technology [CST], MA, USA, 1:1000; p-PI3K, Affinity Biosciences LTD, Jiangsu, China, 1:1000) overnight at 4 °C and probed with secondary antibodies (goat anti-rabbit IgG horseradish peroxidase (HRP), Zhongshan Golden Bridge Biotechnology, Beijing, China, 1:2000) at room temperature for 1 h. The immunoreactive bands were detected using Super ECL Prime (US EVERBRIGHT, Suzhou, China) according to the manufacturer’s protocol.\nCell proliferation was measured through Cell Counting Kit-8 (CCK8, Dojin Laboratories, Kumamoto, Japan) assay. CCK8 assay was carried out according to the standard protocol by seeding cells in a 96-well plate at a density of 1 × 10 5  cells/well. Then 10 μl of the kit reagent was added into each well after 0, 24, 48, 72, 96 h. After incubation for 3 h, the absorbance was measured at 450 nm spectrophotometrically. The experiments were performed in triplicate.\nTo analyze the colony formation, we seeded cells in 35 mm dishes at 6 × 10 3  cells per well in methylcellulose-based MethoCult medium (STEMCELLTM TECHNOLOGIES, Vancouver, British Columbia, Canada). The surviving colonies (≥ 30 cells per colony) were counted under an inverted microscope after 10 days of growing in a humid incubator. All experiments were performed 3 times independently.\nThe cells were inoculated in six-well plates with a density of 1 × 10 5  cells per ml. Then they were synchronized via serum starvation (grown in RPMI 1640 without FBS). After 24 h, the medium was replaced with complete medium for an additional 72 h. The Cell Cycle Staining Kit (Lianke Biotechnology, Hangzhou, China.) was used for cell cycle analyses and the Annexin V-APC/PI Apoptosis Kit (US EVERBRIGHT) was applied for the apoptosis assay. The cell cycle and apoptosis were examined by BD FACSCelesta ™  flow cytometry ( BD  Biosciences, California, USA).\nXenograft model experiments were conducted using 6-week-old male BALB/c nude mice (Beijing HFK Bioscience Co., Ltd.; Beijing, China). All mice were divided into three groups (CTRL, KD1 and KD2), each group consisted of 3 mice. After 2 days of cyclophosphamide intraperitoneal injection (100 mg/kg/d × 2d), the transfected cells were syringed in the mice’s right flank. Tumor volume was calculated every other day for 14 or 18 days using the following formula: volume (mm 3 ) = (L*I 2 )/2, where L and I are the lengthiest and shortest diameters, respectively. Subsequently, all mice were euthanized and the xenograft tumors were harvested, weighed, and photographed. This study was approved by the Ethics Committee of the First Affiliated Hospital of Zhengzhou University.\nThe tissue was fixed in 10% formaldehyde. Firstly, the paraffin sections were deparaffinized. Then the sections were stained with Hematoxylin and Eosin staining solutions. After that, the sections were dehydrated with gradient ethanol, transparentized using xylene. Finally, neutral resin was applied to seal the sections.\nTissue was also fixed in 10% formaldehyde. According to the standard protocol, the paraffin sections were deparaffinized. After repairing antigen and blocking endogenous peroxidase act, tissue sections were blocked in 3% BSA. Tissue sections were incubated with primary antibodies (Ki67, cleaved caspase3, cleaved PARP1, Servicebio, Wuhan, China) at 4 °C overnight, followed by conjugated secondary antibodies (Servicebio, Wuhan, China) and diaminobenzidine (DAB, Servicebio, Wuhan, China). Then nuclei counterstaining was performed with Mayers hematoxylin (Servicebio, Wuhan, China). Finally, the tissue sections were dehydrated and sealed.\nPearson Chi-square test  or Fisher exact analysis was applied for categorical data.  Student’s t-test  or  Mann–Whitney U-test  was applied for continuous variables. Survival was estimated using the  Kaplan–Meier  method and  Log-Rank  test. In the TCGA-LAML, GEO 12,417 and ZZU cohort, patients were classified into the high expression group and the low expression group according to cutoff value of  SMIM3 . A  Cox  proportional hazard regression model was used to determine associations between  SMIM3  transcript levels and OS. Variables with  P  < 0.2 in the single variable analysis were included in the model.  P  <  0.05  (two-sided) was considered significant (*,  P  <  0.05 ; **,  P  < 0.01; ***,  P  < 0.001). The receiver operating characteristic (ROC) curve was generated using the R package “timeROC” [ 37 ] and “survival” ( https://CRAN.R-project.org/package=survival ) to evaluate the diagnostic value. The hazard ratio ( HR ) and corresponding 95% confidence interval ( CI ) were also calculated. Data analysis was performed with Graphpad Prism ™  8.01 (San Diego, California, USA) and R (version 4.1.1, Auckland, NZ, United States,  http://www.r-project.org/ ).\n\nFirst, to identify the role of  SMIM3 , we examined the gene expression in multiple public databases and our cohort (ZZU cohort). We compared the expression of  SMIM3  in GTEX database, UCSC XENA and TCGA database, and results showed that  SMIM3  is significantly overexpressed in 8 cancers, including LAML, and reduced in 16 cancers (Fig.  1 A, B). The ImmuCo database analysis showed that the expression level of  SMIM3  was higher in AML(BMMC) than in hematopoietic stem cell ( P  < 0.0001, Fig.  1 C). Then we investigated the mRNA transcript levels of  SMIM3  in the bone marrow of newly diagnosed subjects with AML and normal healthy individuals in the ZZU cohort. The expression of  SMIM3  in 236 AML patients was significantly higher than in 22 healthy individuals (median 501.55%, Inter Quartile Range  IQR  [264.632–913.75%] vs 160.775%,  IQR  [50.741–220.642%],  P  < 0.001, Fig.  1 D). Fig. 1 AML samples showed a higher expression of  SMIM3  compared to normal samples.  A  Expression levels of  SMIM3  in paired samples of normal and tumor patients in different cancers.  B  In the TCGA-GTEx database,  SMIM3  showed significantly higher expression in AML patients (n = 173) than in normal samples (n = 70).  C  In the ImmuCo database, the gene expression level of  SMIM3  was higher in AML bone marrow mononuclear cells (BMMC, n = 814) than in hematopoietic stem cells (HSC, n = 113).  D  AML samples (n = 236) from the ZZU cohort showed a significant increase in  SMIM3  expression compared to normal bone marrow samples (n = 22).  E \n SMIM3  expression in different cell lines. *,  P  < 0.05; **,  P  < 0.01; ***,  P  < 0.001\nAML samples showed a higher expression of  SMIM3  compared to normal samples.  A  Expression levels of  SMIM3  in paired samples of normal and tumor patients in different cancers.  B  In the TCGA-GTEx database,  SMIM3  showed significantly higher expression in AML patients (n = 173) than in normal samples (n = 70).  C  In the ImmuCo database, the gene expression level of  SMIM3  was higher in AML bone marrow mononuclear cells (BMMC, n = 814) than in hematopoietic stem cells (HSC, n = 113).  D  AML samples (n = 236) from the ZZU cohort showed a significant increase in  SMIM3  expression compared to normal bone marrow samples (n = 22).  E \n SMIM3  expression in different cell lines. *,  P  < 0.05; **,  P  < 0.01; ***,  P  < 0.001\nSubsequently, we analyzed the role of  SMIM3  in the prognosis of AML patients. In TCGA database, patients with high  SMIM3  expression showed a worse 2-year OS than those with low  SMIM3  expression (50.1% [39.4%-63.6%] vs. 36.1% [25.1–51.9%];  P  = 0.018; Fig.  2 A). Moreover, in 69 AML with normal karyotype (NK-AML), patients with high  SMIM3  expression had a worse 2-year OS than those with low  SMIM3  expression (41.1% [26.3–64.0%] vs. 32.8% [18.8–57.0%];  P  = 0.046; Fig.  2 B). The prognostic value of  SMIM3  in NK-AML was also validated in the  GSE12417  cohort ( GPL97  and  GPL570 ). All AML samples in this cohort had normal karyotype. As previously found in the TCGA cohort, H- SMIM3  groups were associated with poor survival outcome (Fig.  2 C, D). Fig. 2 Overall survival (OS) of adult subjects with AML according to  SMIM3 .  A  OS of 151 AML subjects in TCGA.  B  OS of 69 AML subjects with normal karyotype in TCGA.  C  OS of 163 AML subjects in  GSE12417 - GPL97 .  D  OS of 79 AML subjects in  GSE12417 - GPL570 .  G  OS of 95 AML subjects with normal karyotype in ZZU cohort.  H  Differences in OS between the transplant and non-transplant groups in ZZU NK-AML cohort. Overall survival (OS) of adult subjects with AML according to risk-stratification system.  E  OS of 236 AML subjects in ZZU cohort.  F  OS of 95 AML subjects with normal karyotype in ZZU cohort\nOverall survival (OS) of adult subjects with AML according to  SMIM3 .  A  OS of 151 AML subjects in TCGA.  B  OS of 69 AML subjects with normal karyotype in TCGA.  C  OS of 163 AML subjects in  GSE12417 - GPL97 .  D  OS of 79 AML subjects in  GSE12417 - GPL570 .  G  OS of 95 AML subjects with normal karyotype in ZZU cohort.  H  Differences in OS between the transplant and non-transplant groups in ZZU NK-AML cohort. Overall survival (OS) of adult subjects with AML according to risk-stratification system.  E  OS of 236 AML subjects in ZZU cohort.  F  OS of 95 AML subjects with normal karyotype in ZZU cohort\nIn ZZU AML cohort, the present risk stratification had prognostic significance in the entire cohort (Fig.  2 E), but not in the normal karyotype-AML (NK-AML) group (Fig.  2 F). In the whole cohort, the 2-year OS between the low expression group and the high expression group showed no significant difference (42.2%, 95% CI  [35.5–50.2%] vs 35.8% [22.2–57.9%],  P  = 0.186; Additional file  2 : Figure S1). However, in the NK-AML subgroup (n = 95), subjects with low  SMIM3  expression showed a favorable 2-years OS compared with subjects with high  SMIM3  expression (47.0%, 95% CI  [36.3–60.9%] vs 21.1% [8.1–54.9%], P = 0.01; Fig.  2 G). The main clinical characteristics of NK-AML in the ZZU cohort were shown in Additional file  1 : Table S2. Multivariate  Cox  regression showed that  SMIM3  and transplant were independently associated with OS (Table  1 ). We then performed a subgroup analysis in patients with or without transplant, and the result showed that low  SMIM3  group had a favorable OS (Fig.  2 H, P < 0.001) in patients without transplant, but showed no prognostic impact in patients with transplant (Fig.  2 H, P = 0.84) (Additional file  3 ). Table1 Univariate and Multivariate Analysis of Overall Survival in AML with Normal Karyotype characteristics Univariate analysis Multivariable analysis HR  (95% CI ) P -value HR  (95% CI ) P- value SMIM3 2.19(1.19–4.01) 0.011 2.9 (1.51–5.57) 0.001 Age 2.07(1.11–3.85) 0.022 1.58 (0.82–3.02) 0.171 Sex 0.65(0.37–1.14) 0.132 0.74 (0.41–1.32) 0.308 WBC, × 10 9 /L 0.81(0.47–1.41) 0.464 NA NA PLT, × 10 9 /L 1.91(1.09–3.33) 0.023 1.56(0.81–2.98) 0.18 LDH U/L 1.39(0.78–2.49) 0.264 NA NA PB(%) 0.56 (0.28–1.09) 0.087 0.94(0.43–2.08) 0.884 FLT3 1.09(0.6–1.96) 0.784 NA NA FLT3-ITD 1.13(0.63–2.04) 0.678 NA NA FLT3-TKD 0(0-Inf) 0.997 NA NA RUNX1 2.39(0.73–7.79) 0.148 1.56(0.45–5.49) 0.485 ASXL1 1.03(0.54–1.96) 0.94 NA NA CBFβ NA NA NA NA CBL 2.2(0.53–9.12) 0.278 NA NA CEBPA 0.67(0.35–1.27) 0.221 NA NA DNMT3A 0.93(0.47–1.86) 0.835 NA NA ETO NA NA NA NA ETV6 0.64(0.09–4.66) 0.662 NA NA EZH2 0(0-Inf) 0.996 NA NA IDH1 0.68(0.24–1.89) 0.459 NA NA IDH2 0.47(0.12–1.95) 0.302 NA NA JAK2 0(0-Inf) 0.996 NA NA KIT 0(0-Inf) 0.996 NA NA MLL 2.65(0.36–19.52) 0.339 NA NA NPM1 1.12(0.61–2.08) 0.708 NA NA NRAS 0.68(0.29–1.58) 0.367 NA NA PHF6 1.39(0.19–10.19) 0.745 NA NA SETBP1 1.77(0.43–7.3) 0.431 NA NA SF3B1 NA NA NA NA SRSF2 1.16(0.28–4.8) 0.842 NA NA TET2 0.72(0.42–1.24) 0.235 NA NA TP53 0(0-Inf) 0.996 NA NA U2AF1 1.08(0.46–2.53) 0.857 NA NA WT1 0.92(0.52–1.63) 0.855 NA NA ZRSR2 NA NA NA NA Risk 1.15(0.79–1.67) 0.476 NA NA Transplant 0.23(0.08–0.64) 0.005 0.26(0.09–0.76) 0.014 WBC  white blood cell counts,  HGB  hemoglobin,  PLT  platelet,  LDH  lactate dehydrogenase,  PB  peripheral blood\nUnivariate and Multivariate Analysis of Overall Survival in AML with Normal Karyotype\nWBC  white blood cell counts,  HGB  hemoglobin,  PLT  platelet,  LDH  lactate dehydrogenase,  PB  peripheral blood\nTo get further insight into the biological roles of  SMIM3 , in vitro experiments were performed. We then detected the transcriptional level of  SMIM3  in cell lines of hematological malignancies. RT-qPCR suggested that  SMIM3  was over-expressed in acute myeloid leukemia cell lines, while expressed with low level in lymphoma and myeloma cell lines (Fig.  1 E). To further explore the role of  SMIM3  in AML, we constructed  SMIM3  knockdown stable cell lines in Kasumi-1 and THP-1 using lentiviral small hairpin RNAs. The transfection efficiency was verified by RT-qPCR (Fig.  3 A, B) and Immune fluorescence (IF) (Fig.  3 E, F). The results of IF demonstrated that  SMIM3  protein expression was significantly reduced compared with control group after transfection with  SMIM3  shRNA (Fig.  3 E, F). Meanwhile,  SMIM3  primarily localized to the nucleus in AML cells, and was also observed in vesicles (Fig.  3 E, F). CCK8 analysis showed that  SMIM3  knockdown significantly inhibited the proliferation of Kasumi-1 and THP-1 cells compared to the controls (Fig.  3 C, D). Similarly, the anti-proliferative effect of  SMIM3  was observed by colony formation assays (Fig.  3 G, H). Fig. 3 Downregulation of  SMIM3  inhibited cell proliferation and colony formation in AML cells. The efficiency of  SMIM3  knockdown in the Kasumi-1 and THP-1 cell lines was verified by  A ,  B  reverse transcription-quantitative polymerase chain reaction and  E ,  F  immune fluorescence, respectively.  C ,  D  Cell proliferation was detected by the CCK-8 assay in Kasumi-1 and THP-1.  G ,  H  The colony formation of  SMIM3 -CTRL and  SMIM3 -KD in Kasumi-1 and THP-1. CTRL, control; KD, knockdown; *P < 0.05 compared with CTRL cells; **P < 0.01 compared with CTRL cells; ***P < 0.001 compared with CTRL cells; Error bars indicate the standard deviation\nDownregulation of  SMIM3  inhibited cell proliferation and colony formation in AML cells. The efficiency of  SMIM3  knockdown in the Kasumi-1 and THP-1 cell lines was verified by  A ,  B  reverse transcription-quantitative polymerase chain reaction and  E ,  F  immune fluorescence, respectively.  C ,  D  Cell proliferation was detected by the CCK-8 assay in Kasumi-1 and THP-1.  G ,  H  The colony formation of  SMIM3 -CTRL and  SMIM3 -KD in Kasumi-1 and THP-1. CTRL, control; KD, knockdown; *P < 0.05 compared with CTRL cells; **P < 0.01 compared with CTRL cells; ***P < 0.001 compared with CTRL cells; Error bars indicate the standard deviation\nTo clarify the role of  SMIM3  in cell proliferation and apoptosis, flow cytometry was performed. Results revealed that compared to the control group, knockdown of  SMIM3  significantly increased the total apoptosis rate in both Kasumi-1 and THP-1 cells (Fig.  4 A, B). Moreover, knockdown of  SMIM3  increased cell counts in the G0/G1 phase in both Kasumi-1 and THP-1, and decreased cell counts in the S and G2/M phase in Kasumi-1 (Fig.  4 C–E). Furthermore, western blot was performed to assess proteins associated with cell cycle and apoptosis. Knockdown of  SMIM3  resulted in an increase in cleaved-PARP and p27, and a significant decrease in Cyclin D1 and CDK4 (Fig.  4 F–H). Fig. 4 Apoptosis and cell cycle analysis in AML cell lines.  A ,  B  The flow cytometry was applied to analyze apoptosis in  SMIM3  knockdown cells compared with control.  C – E  Propidium iodide (PI) staining was applied to analyze the cell cycle of  SMIM3  knockdown cells compared with control.  F  Alterations in apoptosis and cell cycle-related protein assay in  SMIM3  knockdown cells compared with control.  G ,  H  Densitometric analysis of the WB signals. CTRL, control; KD, knockdown; *P < 0.05 compared with CTRL cells; **P < 0.01 compared with CTRL cells; ***P < 0.001 compared with CTRL cells\nApoptosis and cell cycle analysis in AML cell lines.  A ,  B  The flow cytometry was applied to analyze apoptosis in  SMIM3  knockdown cells compared with control.  C – E  Propidium iodide (PI) staining was applied to analyze the cell cycle of  SMIM3  knockdown cells compared with control.  F  Alterations in apoptosis and cell cycle-related protein assay in  SMIM3  knockdown cells compared with control.  G ,  H  Densitometric analysis of the WB signals. CTRL, control; KD, knockdown; *P < 0.05 compared with CTRL cells; **P < 0.01 compared with CTRL cells; ***P < 0.001 compared with CTRL cells\nAs shown in volcano map (Fig.  5 A), 231 genes (red dots) were significantly upregulated, and 1889 genes (blue dots) were downregulated (|log2(FC)|> 1 & p.adj < 0.05). The top ten up-regulated DEGs and top ten down-regulated DEGs between the high- and low-  SMIM3  groups were displayed in the heat map (Fig.  5 B). Moreover, we screened out some genes that had a high correlation with  SMIM3  (p < 0.5,|r|> 0.3). The Venn diagram (Fig.  5 D) showed the overlap among the DEGs and correlated genes. Further GO and KEGG pathway enrichment analyses of these 655 co-expressed genes were carried out (Fig.  5 C). Cellular components (CC) associated with high  SMIM3  included cation channel complex, ion channel complex, potassium channel complex. Molecular function (MF) associated with high  SMIM3  included Wnt-protein binding, platelet-derived growth factor binding, G protein-coupled receptor binding. KEGG analysis revealed that DEGs were mainly involved in phosphoinositide 3-kinase (PI3K)−AKT signaling pathway, proteoglycans in cancer and cytokine-cytokine receptor interaction. For this study, we chose PI3K −AKT for in vitro and in vivo validation. Fig. 5 GO/KEGG enrichment analysis of subjects with high or low  SMIM3  expression in the TCGA-LAML dataset.  A  Volcano map of the DEGs, including 231up-regulated genes and 1889 down-regulated genes.  B  Heat map showing the top ten up-regulated and the top ten down-regulated genes. The samples are shown on the X-axis, and the DEGs are shown on the Y-axis.  D  Venn diagram of the overlap among the DEGs and correlated genes.  C  GO and KEGG enrichment analysis of the co-expressed genes of DEGs and correlated genes. MF, molecular function. CC, cellular component. BP, biological process. Different categories were shown on the Y-axis, and the X-axis reflected the percentage of DEGs. PI3K-AKT signaling pathway is critical for  SMIM3 -mediated changes.  G  Western blot analysis of PI3K-AKT signaling pathway in  SMIM3 -KD cells and controls.  H ,  I  Densitometric analysis of the WB signals.  E  SC79 (10 mM) reversed the inhibitory effect of  SMIM3  knockdown on the proliferation of Kasumi-1,  F  at 24 h. CTRL, control; KD, knockdown; ***P < 0.001 compared with CTRL cells; Error bars indicate the standard deviation\nGO/KEGG enrichment analysis of subjects with high or low  SMIM3  expression in the TCGA-LAML dataset.  A  Volcano map of the DEGs, including 231up-regulated genes and 1889 down-regulated genes.  B  Heat map showing the top ten up-regulated and the top ten down-regulated genes. The samples are shown on the X-axis, and the DEGs are shown on the Y-axis.  D  Venn diagram of the overlap among the DEGs and correlated genes.  C  GO and KEGG enrichment analysis of the co-expressed genes of DEGs and correlated genes. MF, molecular function. CC, cellular component. BP, biological process. Different categories were shown on the Y-axis, and the X-axis reflected the percentage of DEGs. PI3K-AKT signaling pathway is critical for  SMIM3 -mediated changes.  G  Western blot analysis of PI3K-AKT signaling pathway in  SMIM3 -KD cells and controls.  H ,  I  Densitometric analysis of the WB signals.  E  SC79 (10 mM) reversed the inhibitory effect of  SMIM3  knockdown on the proliferation of Kasumi-1,  F  at 24 h. CTRL, control; KD, knockdown; ***P < 0.001 compared with CTRL cells; Error bars indicate the standard deviation\nBased on the above findings, we screened signaling pathways that could be involved in the function of  SMIM3 . As shown in Fig.  5 G, phosphorylation of PI3K and AKT were notably decreased in  SMIM3  knockdown cells. To further validate the effect of  SMIM3  on PI3K-AKT signaling pathway, the AKT agonist SC79 was used to treat the SMIM3-KD cells of Kasumi-1. The addition of the AKT agonist (SC79) significantly reversed the inhibitory effect of  SMIM3  knockdown on the proliferation of AML cells (Fig.  5 E, F).\nTo validate the effects of  SMIM3  from the in vitro experiments and the involvement of PI3K-AKT signaling pathways, we applied a vivo xenograft model. Our study showed that in Kasumi-1and THP-1 cells, the knockdown of  SMIM3  significantly suppressed tumor growth compared to that in the control group. The tumor formation in nude mice revealed that the volume and weight of tumor in the experimental group with  SMIM3  knockdown were significantly reduced than that of the control group (Fig.  6 A–C, F–H). We also performed Ki67 immunohistochemical staining and  HE  staining to evaluate tumor cell proliferation (Fig.  6 D, I). The result of Ki67 and HE staining confirmed that the knockdown of  SMIM3  inhibited tumor growth. Western blot showed that p-AKT and p-PI3K were significantly decreased (Fig.  6 E, J). These changes in vivo were consistent with the results in vitro. Fig. 6 SMIM3  knockdown reduced the proliferation of AML cells in nude mice by inhibiting PI3K-AKT signaling pathway.  A – D ,  F – I \n SMIM3 -KD inhibits tumor growth in Kasumi-1 and THP-1 cells.  E ,  J  The expression of PI3K-AKT signaling pathway proteins in tumor tissues by Western blot. CTRL, control; KD, knockdown; ***P < 0.001 compared with CTRL cells\nSMIM3  knockdown reduced the proliferation of AML cells in nude mice by inhibiting PI3K-AKT signaling pathway.  A – D ,  F – I \n SMIM3 -KD inhibits tumor growth in Kasumi-1 and THP-1 cells.  E ,  J  The expression of PI3K-AKT signaling pathway proteins in tumor tissues by Western blot. CTRL, control; KD, knockdown; ***P < 0.001 compared with CTRL cells\nMolecular-targeted therapy is a common treatment for AML patients. Moreover, the purpose of our study was to find genes associated with the prognosis of AML, in order to further guide the treatment. Thus, based on a previous study [ 38 ], we compared the distribution of drugs sensitivity represented by the area under the curve (AUC) with the expression level of  SMIM3 . Results indicated that patients with high expression of  SMIM3  were more sensitive to BEZ235, Imatinib, INK–128, Rapamycin, Selinexor, and Sorafenib (Fig.  7 A–C, E–G). Patients with low expression of  SMIM3  were more sensitive to Bortezomib (Fig.  7 D). BEZ235, INK-128 and Rapamycin belong to the family of PI3K-AKT-mTOR inhibitor. Imatinib belongs to the family of tyrosine kinase inhibitor. Selinexor is a small molecule Exportin-1 (XPO1) inhibitor. Sorafenib belongs to the family of RTK inhibitor. Bortezomib is a proteasome inhibitor. Fig. 7 The relationship between drugs sensitivity and the expression level of  SMIM3\nThe relationship between drugs sensitivity and the expression level of  SMIM3\n\nThis study investigated the prognostic value and molecular mechanism of  SMIM3  in adult AML. Based on the bioinformatics analyses and our clinical data, we found that adult AML patients showed a significant increase in the expression level of  SMIM3  compared with normal controls. In NK-AML, the high  SMIM3  expression was independently associated with a poor prognosis. To highlight the function of  SMIM3  in AML, we further explored the critical effects of  SMIM3  on cell behaviors through both in vivo and in vitro experiments. Our results suggested that the knockdown of  SMIM3  could inhibit cell proliferation and colony formation, arrest cell cycle progression and promote apoptosis. The effect on cell proliferation may occur through downregulating PI3K-AKT signaling pathway.\nWe performed a pan‐cancer expression analysis of  SMIM3  and showed that  SMIM3  was highly upregulated in 8 cancers and commonly downregulated in 16 cancers. This suggests that  SMIM3  has complex regulatory roles, and can act as either a potential oncogene or a tumor suppressor gene in different cancer types. The high expression of  SMIM3  in AML was also further validated in GEO database, ZZU cohort and cell lines.\nCurrent studies found multiple connections between  SMIM3  and various diseases, including pheochromocytoma [ 27 ], 5q- syndrome of MDS [ 28 ] and radiation exposure [ 29 ]. There are few studies on the biological functions of  SMIM3  in different cancers. A study revealed that  SMIM3  may be associated with poor prognosis in oral squamous cell carcinoma [ 30 ], which needs to be further verified. Interestingly, membrane proteins with a similar structure to  SMIM3  (such as the minK family [ 39 ], the γ subunit of the Na, K-ATPase [ 40 ,  41 ] and phospholamban [ 42 ]) are thought to play a regulatory role in ion channel subunits, suggesting that  SMIM3  may have a similar role [ 28 ]. However, there has not been any in-depth study in the function of  SMIM3  yet. Until now, the upstream and downstream mechanisms of  SMIM3  expression remain unclear. Based on our current results, we would like to further investigate molecular mechanisms in future studies. What’s more, no SMIM family gene has been studied in AML. But several genes do play a role in other cancers. This suggests that SMIM family may play a role in cancers. Further studies should be carried out to define the function of these genes in AML.\nThe wide application of the existing risk stratification diagnosis and treatment has improved the prognosis of AML patients. Even though the risk stratification system was associated with adult AML prognosis in our cohort, no significant survival difference was found in NK-AML. This indicated the need to improve the risk stratification for NK-AML patients. Our study revealed that high expression of  SMIM3  was associated with worse OS in NK-AML. This result was confirmed in several databases. Moreover, multivariate survival analysis indicated that high  SMIM3  expression and transplant were independent prognostic factors for unfavorable OS in ZZU NK-AML cohort. NK-AML patients without transplant had a poor prognosis in H-  SMIM3  group, but there was no significant difference in the allo‐HSCT subgroup. This result suggested that allo‐HSCT may be an effective way to overcome the adverse impact of  SMIM3 . Collectively, these results suggested that  SMIM3  might be a novel prognostic marker for NK-AML patients.\nThe abnormally high expression and poor prognosis suggested the biological functions of  SMIM3  in AML. Our study provided further evidence that  SMIM3  affected the proliferation of AML cells through apoptosis and cell cycle regulation both in vitro and in vivo. The results of IF revealed that  SMIM3  was mainly localized in the nucleus. The knockdown of  SMIM3  caused G0/G1 cell cycle arrest via the p27/Cyclin D1-CDK4 pathway. The induction of p27, a cyclin dependent kinase inhibitor, caused cell cycle progression at the G0/G1 phase [ 43 – 46 ]. Also, G0/G1 phase is regulated by CDK4 and Cyclin D1 [ 47 – 49 ]. The upregulation of p27 could inhibit the activity of Cyclin D1-CDK4 [ 45 ]. To further understand the mechanism of the biological functions, we studied the changes in critical signaling pathways related to proliferation, apoptosis and metabolism based on KEGG analysis in AML cell lines. The PI3K-AKT signaling pathway plays a central role in metabolism. It regulates crucial functions including proliferation, differentiation, and survival [ 50 ]. The activation of this pathway was suggested to be associated with adverse prognosis [ 51 ]. Our results showed that the phosphorylated PI3K-AKT was reduced in the  SMIM3 -KD cells. These suggested that  SMIM3  could modulate the growth and survival of AML cells by regulating the PI3K-AKT signaling pathway. Based on a previous database, we found that the H- SMIM3  group was more sensitive to PI3K-AKT-targeted drugs. These were consistent with KEGG, in vitro and in vivo results. Additionally, H- SMIM3  group was also more sensitive to various first-line and novel drugs, including Imatinib, Selinexor, Sorafenib and Bortezomib. These results provided the basis for the application of targeted drugs, which could reduce the chance of relapses and drug resistance. In addition, GO and KEGG pathway enrichment analyses also found that cation channel complex, ion channel complex and potassium channel complex were associated with high  SMIM3.\nThere are still some drawbacks in our study. Firstly, our study had the inherent limitations of any retrospective study. Secondly, our results need to be further verified in multicenter large sample prospective cohort studies.\n\nIn summary, this was the first study to elucidate the significance of  SMIM3  in adult AML. Our study indicated that high expression level of  SMIM3  was associated with poor OS in adults NK-AML patients. In addition, knockdown of  SMIM3  inhibited proliferation and cell cycle progression, and induced apoptosis of AML cell lines through downregulating PI3K-AKT signaling pathway. These findings provided evidence that  SMIM3  may serve as a potential prognostic marker and personalized treatment target for AML in the future.\n\nAdditional file 1: Table S1.  Sequences of primers and probes used in this study.  Table S2.  Relationship between Transcription Level of SMIM3 and Clinical Characteristics in Normal Karyotype AML.  Table S3 . The catalog number of reagents. Additional file 2: Figure S1.  Overall survival (OS) of adult subjects with AML according to SMIM3. OS of 236 AML subjects in ZZU.(We didn't find our Figure S1 in the file, do we need to upload the Figure S1 again?)  Figure S2.  Immunohistochemical analysis of tissues in tumor tissues. Additional file 3.\nAdditional file 1: Table S1.  Sequences of primers and probes used in this study.  Table S2.  Relationship between Transcription Level of SMIM3 and Clinical Characteristics in Normal Karyotype AML.  Table S3 . The catalog number of reagents.\nAdditional file 2: Figure S1.  Overall survival (OS) of adult subjects with AML according to SMIM3. OS of 236 AML subjects in ZZU.(We didn't find our Figure S1 in the file, do we need to upload the Figure S1 again?)  Figure S2.  Immunohistochemical analysis of tissues in tumor tissues.\nAdditional file 3.","source_license":"CC-BY-4.0","license_restricted":false}