Introduction
B-cell acute lymphoblastic leukemia (B-ALL) is an aggressive type of acute leukemia characterized by the clonal expansion of immature B cells and extensive extramedullary infiltration [
1]. B-ALL patients cover different age groups and genders, but clinical outcomes vary from children to adults [
2]. In general, the prognosis of adult patients is far worse than that of children [
2]. Lower treatment responses of adult patients are attributed to the heterogenic transcriptome, pre-existing comorbidities, and poor tolerance of chemotherapies [
3,
4]. Although remission rates are appreciable, long-term maintenance of complete remission (CR) can still be ruined by bone marrow (BM) recurrence [
5]. Given the special situation, treatment regimens for refractory/relapse (R/R) B-ALL remain undetermined [
6,
7]. Recently, targeting tumor immunity has been regarded as a critical approach to improving therapeutic efficacy [
8,
9]. Based on the capability of regulating immune cell activation, chimeric antigen receptor T (CAR-T) cells and immune checkpoint inhibitors have achieved impressive efficacy in patients with R/R B-ALL [
10,
11]. Therefore, molecular mechanisms of tumor immunoregulation associated with tumorigenesis and progression deserve in-depth exploration.
Tissue-specific tumor microenvironment (TME) is a crucial factor in anti-tumor immune response [
12,
13]. Accumulating evidence has considered the stimulator of interferon genes (STING, also named TMEM173) as a vital regulator in immunoregulation [
14,
15]. TMEM173 has a well-known role in innate immunity via regulating immune cells and signaling pathways [
16,
17]. On the one hand, TMEM173 activation contributes to establishing crosstalk between tumor cells and TME cells, further leading to TME remodeling [
18] and anti-tumor response [
19‐
21]. Hence, TMEM173 agonists have been approved for several pre-clinical models and clinical trials [
22], especially in patients with advanced and refractory tumors [
23‐
25]. On the other hand, TMEM173 has been reported to negatively regulate B cell receptor (BCR) signaling in both normal and malignant B cells [
26]. At present, the biological function of TMEM173 in high-risk B-ALL remains unknown.
Increasing studies highlight the importance of transcriptional heterogeneity in tumorigenesis, which is associated with functional changes in cell viability, distant metastasis, and drug resistance [
27,
28]. Identification of cell-specific genes and TME features provides insights into the mechanisms of tumorigenesis and tumor progression [
29,
30]. Single-cell RNA sequencing (scRNA-seq) is a new technology of high-throughput sequencing analysis, which can be used to interrogate features of tumor tissues at a single-cell resolution [
31,
32]. In this study, scRNA-seq analysis was performed to investigate the transcriptomic features of TMEM173 in high-risk B-ALL patients, which profiled the differential expression of TMEM173 in BM cells. Specifically, proliferated precursor-B (pre-B) cells, cytotoxic natural killer (NK) cells, and activated dendritic cells (DCs) expressed low levels of TMEM173. This characterization facilitated understanding biological functions of TMEM173 and enabled the identification of new targets for immunotherapy.
Methods
Peripheral blood samples
Peripheral blood samples were obtained from 6 newly diagnosed B-ALL patients and 3 healthy donors in Shandong Provincial Hospital. Clinical data of enrolled patients and healthy donors were presented in Table
1. The diagnostic criteria were established according to the World Health Organization (WHO) classification [
33]. Peripheral blood mononuclear cells (PBMCs) were isolated using the Ficoll-Hypaque density gradient centrifugation method (TBD Science, China) [
34]. PBMCs of 3 healthy donors were labeled by Normal (N) while 6 patient samples were labeled by Tumor (T). In accordance with the Helsinki declaration, the acquisition of clinical samples complied with the informed consent. This study was approved by the Medical Ethical Committee of Shandong Provincial Hospital.
Table 1
Clinical features of 6 B-ALL patients and 3 healthy donors
T1 | Female | 49 | B-ALL | TP53, ZEB1, BCORL1, SPEN, KLF2, FAT1, FOXO3, KMT2C | 47, XX, + 1 der(1;16)(q10;p10), + 8, t(9;22)(q34;q11.2) [3] | 134.13 | 94 | Diagnosis |
T2 | Male | 15 | B-ALL | ETV6, KRAS, EZH2 | - | 21.48 | 93 | Diagnosis |
T3 | Male | 67 | Pre-B ALL | KRAS, NF1, PTEN, DNM2, TCF3, TP53 | 73 ~ 79 < 3n>,XXY, + 1, +4,+6, + 8, add(9)(p22); +16, + 17, -17, + 19, +21, + 22, inc [cp4] | 5.69 | 99 | Diagnosis |
T4 | Female | 56 | B-ALL (High-risk) | KRAS, NF1, PTEN, DNM2, TCF3, TP53 | 46,XX,t(2;12)(p13;p11),del(8)(p21) [6] /46,XX [4] | 17.17 | 95 | Diagnosis |
T5 | Male | 46 | Ph-positive B-ALL (High-risk) | BCR-ABL1 | 46, XY, t(9;22)( (q34;q11) [10] | 52.69 | 90 | Diagnosis |
T6 | Female | 64 | Ph-positive B-ALL (High-risk) | BCR-ABL1, SF1, USP7, SPIB, PLCG1, SF3A1, EP300, POT1, PTPRD | 46, XX, t(9;22)( (q34;q11) [2] | 57.35 | 96 | Diagnosis |
N1 | Female | 30 | | | | | | |
N2 | Male | 25 | | | | | | |
N3 | Male | 27 | | | | | | |
Quantitative real-time PCR (qRT-PCR)
Total RNA was extracted from each PBMC sample (N = 3, T = 6) by the TRIzol reagent (TaKaRa, 9108-1, Japan). After removing the genomic DNA from RNA templates, RNA was reverse transcribed into cDNA using HiScript III RT SuperMix (Vazyme, R323-01, China). Amplification reactions were performed in Light Cycler 480II (Roche) with the FastStart™ Universal SYBR Green (Roche, Switzerland) [
35,
36]. Reactions were carried out for 30 s at 95°C, followed by 50 cycles of PCR for 10 s at 95 ℃, 20 s at 55 ℃, and 20 s at 72 ℃. Data were evaluated using the 2
−ΔΔCt method. Primers of TMEM173: Forward, 5’-TACAACAACCTGCTACGGGG-3’; Reverse, 5’-TCTGCTGGGGCAGTTTATCC-3’. Primers of GAPDH: Forward, 5’-GGTGAAGGTCGGAGTCAACG-3’; Reverse, 5’-CAAAGTTGTCATCGAATGAC-3’. Primers of β-actin: Forward, 5’-CATGTACGTTGCTATCCAGGC-3’; Reverse, 5’-CTCCTTAATGTCACGCACGAT-3’.
Sanger sequencing
Total RNA was extracted from PBMCs of B-ALL (T = 6), followed by genomic DNA wiper and reverse transcription. Sanger sequencing was performed by the BioSune Technology Co., Ltd. (Shanghai, China) according to the manufacturer’s protocol.
Western blotting (WB)
WB was performed as previously described [
37,
38]. Briefly, cell lysates of each PBMC sample (N = 3, T = 6) were resolved by 10% SDS-PAGE and transferred onto polyvinylidene fluoride (PVDF) membranes. Full-length PVDF membranes were blocked in 10% milk in Tris-buffered saline and Tween 20 (TBST), and incubated with primary antibodies (1:1000) overnight at 4℃. Nitrocellulose-bound primary antibodies were combined with HRP-linked secondary antibodies (1:5000). Chemiluminescent signals were detected by the Amersham Imager 680 (GE Healthcare, UK). After performing 3 replicate experiments, expression levels of protein were represented by gray values and calculated by the Image J software (National Institutes of Health, USA). Primary antibodies were listed as follows: anti-rabbit TMEM173 (Cell Signaling Technology, 13647, USA) and anti-mouse GAPDH (Zhongshan Gold Bridge, TA-08, China).
Linear dimensionality reduction and cell clustering
ScRNA-seq data of 2 healthy donors and 2 high-risk B-ALL patients was obtained from the Gene Expression Omnibus (GEO) database (GSE130116, Supplementary Table 1). ScRNA-seq data of each patient included BM cells at the time of initial diagnosis and relapse (Supplementary Table 1). Original data was loaded into Seurat version 3.6.3 and processed by the Seurat package. Firstly, scRNA-seq data was fully merged by the Harmony package, followed by data filtering, normalization, and removal of batch effects. For data filtering, genes detected in less than 3 cells or with counts of zero across all cells were excluded. Data normalization was then conducted by the NormalizeData function and the global-scaling log-normalization with a scale factor of 10,000. Subsequently, 4,000 high-variable genes were extracted using the FindVariableGenes function, followed by the identification of principal component analysis (PCA) and principal components (PCs). Based on the ElbowPlot function, the top 50 PCs were screened for cell clustering. Finally, t-distributed stochastic neighbor embedding (t-SNE) was applied to realize cell clustering.
Cell type annotation and genes expression analysis
Cell type annotation was conducted by a combination of the FindAllMarkers function and the CellMarker (
http://biocc.hrbmu.edu.cn/CellMarker/index.jsp). Marker genes of each cluster were extracted by the FindAllMarkers function and subsequently introduced into the CellMarker to distinguish cell types. The typical marker genes of each cell cluster were listed in
Supplementary Tables 1 and exhibited by heatmap plots. The FeaturePlot, VlnPlot, DotPlot, and RidgePlot functions were used to analyze gene expression features. Besides, differentially expressed genes (DEGs) were illustrated using volcano plots. Finally, pseudo-time analysis performed by the Monocle package was applied to display cell development trajectory and gene expression features over time.
Statistical analysis
All data are recorded using mean ± standard deviation (SD) from at least three separate experiments. The GraphPad Prism software (v8.0a, La Jolla, CA, USA) was applied to the statistical analysis. The relative expression of mRNA and the grayscale values of protein were confirmed to be normally distributed. The statistical significance between the two groups was thereby determined by the unpaired two-tailed T-test with assumed normal distribution. P < 0.05 was considered statistically significant. *P < 0.05, **P < 0.01.
Discussion
In this present study, we first explored the transcriptome features of TMEM173 in BM cells of high-risk B-ALL at a single-cell resolution. TMEM173 was differentially expressed in BM cells, of which B cells, NK cells, and DCs were featured with low levels of TMEM173. On the one hand, proliferated pre-B cells featured low levels of TMEM173 and downstream pyroptosis effector GSDMD during the progression of B-ALL. On the other hand, TMEM173 expression was associated with the functional activation of NK cells and DCs. Our findings indicated the potential role of TMEM173 in the anti-tumor therapy of B-ALL.
TMEM173 plays a significant role in tumorigenesis, anti-tumor immune response, and cell death induction. Notably, recent studies demonstrate that TMEM173 is involved in the development of acute leukemia. Activation of TMEM173 depresses the hematopoietic capacity of hematopoietic stem cells (HSCs) and the viability of acute myeloid leukemia (AML) cells [
48,
49]. Our results identify the low levels of TMEM173 in malignant B cells, which meet the demands of rapid cell proliferation. In addition to cell viability, various kinds of cell death are under the regulation of TMEM173 [
50]. In particular, TMEM173 is involved in pyroptosis, of which the canonical pathway depends on TMEM173-mediated GSDMD cleavage [
51,
52]. Inducing pyroptosis in tumor cells has been regarded as an effective strategy for reducing tumor burden [
53,
54]. For B-ALL, tumor burden mainly derives from the clonal expansion of malignant B cells [
55]. Notably, a portion of pre-B cells restrains the expression of GSDMD with B-ALL progression, indicating the possibility of triggering GSDMD-dependent pyroptosis in leukemic cells. Besides, GSDMD is mainly expressed in pre-B cells with multiplication capacity, represented by high expression of NF-κB, CD19, and BTK. It is well known that activation of NF-κB and the CD19-BTK axis is essential for promoting B cell growth [
56,
57]. Herein, targeted activation of TMEM173 in leukemic cells may induce GSDMD-dependent pyroptosis and reduce the tumor burden of B-ALL.
R/R B-ALL is a critical challenge in clinical practice since the prognosis for adult R/R B-ALL remains poor. In a recent study, Tang et al. illustrated that combining cell pyroptosis and immunotherapies significantly enhanced the anti-tumor effects, especially in drug-resistant cases [
58]. CAR-T cells targeting the CD19 antigen represent an innovative therapeutic approach for R/R B-ALL [
59,
60]. Besides, anti-CD19 CAR-T therapy is demonstrated to induce GSDMD-mediated cell pyroptosis in B cell-derived tumor cells [
61]. Given that CD19 is co-expressed with GSDMD in pre-B cells, the combination of anti-CD19 CAR-T cells and TMEM173 agonists will hopefully magnify the efficiency of CAR-T cell therapies in B-ALL.
TME-infiltrating immune cells are the other essential regulators in enhancing the efficacy of anti-tumor therapies [
16]. Consistently, our investigations identify an increase of NK cells and DCs in the BM of B-ALL. Activation of NK cells has been reported to improve the therapeutic efficiency through inducting tumor cell death [
62‐
64]. We consistently demonstrate that cytotoxic NK cells of B-ALL were marked by increased TMEM173, which indicated the importance of TMEM173 in activating the anti-tumor functions of NK cells. DCs are the other component in anti-tumor immune response [
65]. ScRNA-seq analysis reveals an increase in cDC1s and pDCs with immune activation phenotypes in the BM of B-ALL. Accumulating cDC1s is essential for the T cell-mediated anti-tumor response [
66], while pDCs contribute to IFN-α/β secretion [
67]. Activation of TMEM173 in cDC1s and pDCs promotes the recruitment and functional activation of DCs in TME [
16,
68], further improving clinical outcomes [
69]. Accordingly, TMEM173 is consistent with immune activation phenotypes of DCs in B-ALL, suggesting that TMEM173 activation might be associated with enhanced anti-tumor functions of DCs. Therefore, targeted activation of TMEM173 in immune cells is expected to be a feasible strategy for improving therapeutic efficiency and clinical outcomes in B-ALL.
A recent study demonstrates that gene mutations impact the functions of TMEM173 in regulating immune activation [
70]. Although the TMEM173 locus is absent in our next-generation sequencing (NGS) panels, Sanger sequencing identifies frameshift mutation in PBMCs of several B-ALL patients. However, the correlation between mutations and expression of TMEM173 could not be assessed due to insufficient samples. Increasing the number of patient samples and targeted sequencing panels is the focus of future research.
Overall, our findings extend the understanding of the transcriptome features of TMEM173 in B-ALL. It is worth noting that TMEM173 agonists exhibit pronounced anti-tumor effects in advanced solid tumors and lymphomas [
71]. However, the transcriptome landscape cannot demonstrate the biological function of TMEM173 in B-ALL. More functional experiments will be performed in subsequent research to confirm the importance of TMEM173 in B-ALL.
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