Stem cell factor SALL4, a potential prognostic marker for myelodysplastic syndromes

We first evaluated the expression of SALL4 in primary MDS patients by analyzing MDS gene expression profiles from the public database GSE13159[33]. The data was presented as log-transformed scaled signal (DS signal)[34]. We noticed that SALL4 expression measured by microarray was higher (p<0.001) in MDS patients (88.49±77.57, n=206) than that from normal controls (50.54±34.13, n=73) (Figure1A).

We next chose 55 newly diagnosed MDS patients, 20 MDS-AML patients and 16 post-treatment MDS patients for our study and the clinicopathological profile of these patients was summarized in Table 1. The expression level of each gene was presented as 2^-ΔΔCT relative quantitative values. Our results demonstrated that SALL4 mRNA expression level in MDS patients (23.88±21.59, n=55) was significantly higher (p<0.001) than that from the healthy control group (1.02±0.19, n=10). Furthermore, SALL4 expression increased significantly (p<0.001) in MDS-AML (AML patients with history of MDS) patients (74.35±20.00, n=20), but deceased (p<0.05) in post-treatment MDS patients (4.66±4.43, n=16) (Figure1B).

Because MDS is a group of heterogeneous diseases, different subtypes and risk groups exhibit great heterogeneities. We next evaluated SALL4 expression in different WHO morphology and IPSS risk groups and compared expression with that of Bmi-1. Between different MDS subtypes by WHO classification, the expression of SALL4 was significantly higher (p<0.001) in RAEB-1 (35.06±16.32, n=14) and RAEB-2 (45.66±16.87, n=13) subtypes when compared with healthy control, but not refractory cytopenia (RA) (6.62±7.21, n=18) or refractory cytopenia with multilineage dysplasia (RCMD) (8.95±9.72, n=10). Similarly, higher (p<0.001) expression of Bmi-1 was also preferentially seen in RAEB-1 (22.47±11.89, n=14) and RAEB-2 (33.92±19.00, n=13) (Figure 2A). Likewise, between different risk groups of MDS based on IPSS, Int-1 (11.19±10.35, n=25), Int-2 (40.97±12.36, n=12) and High risk groups (52.37±15.65, n=9) had higher (p<0.05) SALL4 expressions than healthy control. As for Bmi-1 expression, Int-2 (28.77±13.00, n=12) and High risk group (36.77±18.97, n=9) showed significantly higher (p<0.001) levels than healthy control (Figure 2B). Furthermore, we performed western blots to see SALL4 and Bmi-1 expression on protein level and found that the protein expression of these two genes followed the same trend (Figure 2C). However, semi-quantitatively analysis demonstrated that this trend was statistically significant for SALL4 (p<0.01) but not Bmi-1 (p>0.05) (Figure 2D).

To investigate the potential value of SALL4 in the clinical diagnostic application of MDS patients, we next conducted Spearman’s correlation analysis on the mRNA expression of SALL4 and clinical parameters. Our results showed that SALL4 was positively correlated with bone marrow blast counts, IPSS score and expression level of Bmi-1 (Table 2). In addition, we observed that SALL4 expression was higher (p<0.001) in MDS patients with high risk (50.14±14.44, n=15) karyotypes according to IPSS, including complex karyotypes (n=14) and chromosome 7 abnormalities (n=1), but lower (p<0.001) in patients with intermediate (15.53±18.62, n=8) and low risk (13.02±11.51, n=32) karyotypes (Figure 3).

During our over 2 years’ follow-up, 11 of 27 (40.74%) RAEB-1/RAEB-2 patients experience disease progression. SALL4 expression of these cases (54.27±14.71, n=11) was significantly higher (p<0.01) than those without disease progression (30.47±10.89, n=16). 14 patients died of MDS or AML progressed from MDS. Since both IPSS and WHO have been used to guide clinical diagnosis and management of MDS patients, we first conducted Kaplan-Meier survival analysis for MDS patients based on WHO subtypes and IPSS risk groups. Based on WHO subtypes, the RAEB-2 group that showed high SALL4 and Bmi-1 expression had a worse (p<0.01) survival rate than other subtypes (Figure 4A). Based on IPSS risk groups, Int-2 and High risk patient groups whose SALL4 and Bmi-1 expression levels were higher than that from Int-1 and Low risk patient groups exhibited a worse (p<0.01) survival rate (Figure 4B). Intriguingly, we noted that among the Int-2 risk group, patients who passed away during the follow up (53.42±11.25, 4 of 12) had higher (p=0.0056) SALL4 expression than those who were still alive at the end of the study (34.75±7.82, 8 of 12). This trend was also observed for Bmi-1 expression. Patients who passed away in the Int-2 risk group had higher Bmi-1 expression (30.91±4.78, 4 of 12), while patients who were still alive had lower Bmi-1 expression (27.69±15.87, 8 of 12). However, this difference was not significant (p=0.7058).

We further conducted Kaplan-Meier survival analysis for MDS patients based on Bmi-1 or SALL4 expression level (The group with high Bmi-1 or SALL4 expression had Bmi-1 or SALL4 mRNA expression that was equal to or exceeded the mean value detected by qRT-PCR, where as the group with low Bmi-1 or SALL4 expression had Bmi-1 or SALL4 mRNA expression that was lower than the mean value). MDS patients with high Bmi-1 or SALL4 expression levels showed a worse (p<0.01) survival rate than low Bmi-1 or SALL4 group (Figure 4C-D). These results suggest that SALL4 and/or Bmi-1 expression could be used as an additional confirmation/refinement for the WHO/IPSS system or even as single or combined molecular tests to help predict the prognosis of MDS. More detailed analysis, however, showed minor differences between the Bmi-1 and SALL4 expression in the survival rate of MDS patients. There was no patient death with low SALL4 expression (Figure 4D), but 3 patients died with low Bmi-1 expression (Figure 4C). This result suggested that SALL4 might be a better molecular marker than Bmi-1, in predicting MDS patient prognosis; however a large cohort study is needed to confirm this result.

THP-1 Human Monocytic Leukemia Cells (Cell Center, Institute of Basic Medical Sciences, Chinese Academy of Science) were cultured in RPMI 1640 supplemented with 10% fetal bovine serum.

Bone marrow samples from 55 newly diagnosed MDS patients, 20 MDS-AML patients, 16 post-treatment MDS patients and 10 healthy donors were collected in Beijing from December 2009 to December 2011. This study was approved by the institutional review board of Peking Union Medical College Hospital. The diagnosis of MDS was based on the 2008 World Health Organization (WHO) Classification[37]. Patients with low or Int-1 IPSS risk received clinical monitoring and relevant supportive care. In general, patients with symptomatic anemia or severe thrombocytopia were treated with relative transfusion. Recombinant human Epo with or without recombinant human granulocyte colony stimulating factor (G-CSF) were used for patients with serum erythropoietin (EPO) levels ≤500 mU/ml. Azacytidine or decitabine were used for patients with thrombocytopenia or neutropenia. For patients with del (5q) chromosomal abnormalities, Lenadomide was used for treatment. Int-2 or high risk patients received high intensive therapy including intensive chemotherapy (such as azacytidine and decitabine) or allogeneic hematopoietic stem cell transplantation (HSCT) if available. For patients who were not suitable (e.g., patient’s age, performance status and patient’s preference) for intensive therapy, relative supportive care was given. Bone marrow samples from post-treatment MDS patients were collected after the patients completed at least two-course treatment.

The 206-MDS-cohort was downloaded from Gene Expression Omnibus (GEO) dataset[38] under series accession number GSE13159. The data in this microarray was presented as log-transformed scaled signal (DS signal)[34].

Red blood cell lysis buffer was used to isolate nucleated cells from bone marrow samples according to a standard procedure. The isolated nucleated cells were then divided into two parts, one of which was conducted with Trizol reagent (Invitrogen) for RNA analysis, the other of which was processed with Cell Lysis Buffer (Beyotime Biotchnology, China) for further protein analysis.

Total RNA was extracted with Trizol reagent (Invitrogen) and treated with DNase. Reverse transcription and PCR amplification were performed according to manufacturer’s instruction (DRR036 and DRR091, TaKaRa). All of the reactions were run in triplicate. The expression level of each gene was normalized to the housekeeping gene β-actin and analyzed by 2^-ΔΔCT relative quantitative method. The sequences of primers were as follows: SALL4 (amplicon length, 68bp; targated Exon2 of human SALL4), forward primer 5′-TGCAGCAGTTGGTGGAGAAC-3′, reverse primer 5′-TCGGTGGCAAATGAGACATTC-3′[18]; Bmi-1 (amplicon length, 198 bp), forward primer 5′-TGGACTGACAAATGCTGGAGA-3′, reverse primer 5′-GAAGATTGGTGGTTACCGCTG-3′; β-actin (amplicon length, 124 bp), forward primer 5′-TGTACGCCAACACAGTGCTG-3′, reverse primer 5′-TCAGGAGGAGCAATGATCTTG-3′.

Western blot was performed according to standard techniques. The following antibodies were used: SALL4 (ab29112, Abcam), Bmi-1 (05–637, Mlillipore), and β-actin (TA-09, ZSGB-BIO, China). The dilution ratio of SALL4 was 1:1000, Bmi-1 1:1000 and β-actin 1:2000.

Statistical analyses were performed using SPSS software package Version 12.0. P-values of <0.05 were considered statistically significant. Data were presented as means ± standard deviation. Unpaired t-test or Mann–Whitney test was used to study difference between two groups. One-Way ANOVA or Kruskal-Wallis test were applied to study differences between more than two groups. When significance was found, Bonferroni’s multiple comparison test or Dunnett’s multiple comparison test was used as a post hoc test. Correlation analysis was performed using the Spearman’s rank correlation coefficient r_s. Survival curves were constructed using the Kaplan-Meier method and compared using the log-rank test.