Fig 2: Decreased expression of DDX3 is associated with poor differentiation of tissue in HCC patients.(a) High HCC grade showed significant reduction of DDX3. Expression level of DDX3 in HCC tissues of total 44 samples extracted from the Ye dataset in the cancer clinical microarray database Oncomine were grouped according to histological grade (Grade 2, 3 and 4), and number of samples in each grade is shown. DDX3 expression is presented as Log2 median-centered ratio. The statistical result of DDX3 level with different HCC grade was analyzed by outlier analysis. (b) Poor survival probability was observed in HCC patients with reduced DDX3 expression. The patients in the Ye dataset were grouped by non-reduced and reduced expression of DDX3, and their survival probability was assessed by Kaplan-Meier estimator. p < 0.05 represents statistical significance. (c) DDX3 expression decreases with the progression of HCC. DDX3 mRNA level in normal as well as HCC tissues of Grade 1, 2 and 3 acquired from OriGene TissueScan Liver Cancer cDNA Array was evaluated by qRT-PCR. Level of DDX3 mRNA in HCC samples was transformed into fold change relative to that of normal samples. Statistical analyses were carried out by t test. p < 0.05 represents statistical significance. (d) High HCC grade was associated with down-regulation of DDX3 and up-regulation of pluripotency factors. Lysates (100 µg each) of representative HCC tissues acquired from TLCN were analyzed by immunoblotting using anti-DDX3, Nanog, Oct4, c-Myc, Sox2 and ß-actin antibodies.

Fig 3: DDX3 suppresses stemness gene signature.(a) Lower expression of DDX3 along with overexpression of stemness markers was observed in the poorly differentiated cell line. Cell lysates (50 µg) of HepG2, Hep3B, HuH-7 and SK-Hep-1 cells were analyzed by western blotting with antibodies against DDX3, Nanog, Oct4, c-Myc, Sox2, KLF4, Bmi1, CK19 and ß-actin. (b) Knockdown of DDX3 led to up-regulation of stemness markers. Cell lysates (50 µg) of stable shLuc, shDDX3 #2 and shDDX3 #3 HepG2 cells were analyzed by western blotting with antibodies described in (a). (c) DDX3 overexpression suppressed stemness markers. Plasmid pcDNA3-SRa/FLAG or pcDNA3-SRa/FLAG-DDX3 was transfected into SK-Hep-1 cells. At 48 h post transfection, cell lysates were prepared and subjected to immunoblotting with antibodies described in (a) and anti-FLAG antibody. ß-actin was used as internal control in (a–c). (d) DDX3 knockdown was correlated with up-regulation of hepatic CSC surface markers. mRNA expressions of DDX3, CD133, CD13, EpCAM, CD90 and GAPDH in shLuc, shDDX3 #2 and shDDX3 #3 cells were detected by qRT-PCR. GAPDH was used as internal control. Fold change of each mRNA transcript in shDDX3 #2 and shDDX3 #3 cells was relative to that of shLuc cells. (e) DDX3 overexpression resulted in suppression of hepatic CSC surface markers. SK-Hep-1 cells were transfected with plasmid pcDNA3-SRa/FLAG or pcDNA3-SRa/FLAG-DDX3 as described in (c). At 48 h post transfection, total RNA was extracted and subjected to qRT-PCR analysis. GAPDH was used as internal control. Fold change of each mRNA transcript in FLAG-DDX3-expressing cells was relative to that of vector control cells. All experiments were performed at least three times, and the error bar indicates ± 1 s.d. of the mean. Statistical analyses were carried out using t test (*p < 0.05; **p < 0.01; ***p < 0.001).

Fig 4: Characterization of zebra fish iPS-like cells. (A) RT-PCR analysis of exogenous rTTA, oct4, sox2, klf4 and c-myc in zSEFs and zFFs at 7-day post-transduction. At least three independent experiments were conducted for these results). (B) RT-PCR analysis of endogenous oct4, sox2, lin28, and nanog in the E-ziPSCs (passage 20) and F-ziPSCs (passage 18) (At least three independent experiments were conducted for these results). (C) Immunofluorescence staining of Oct4, Nanog, and Sox2 in E-ziPSCs (passage 20) (Scale bars represent 20 µm). (D) Immunofluorescence staining of Oct4, Nanog, and Sox2 in F-ziPSCs (passage 18) (Scale bars represent 20 µm). (E) Distribution of chromosome numbers among 100 F-ziPSCs metaphases (passage 18-30). (F) A metaphase plate of the chromosomes of a diploid F-ziPSC (2n = 50) after Giemsa staining (Scale bar represents 10 µm). (G) Diploid karyotype of an F-ziPSC (homologous chromosomes were paired according to their sizes).

Fig 5: Derivation of cancer stem cells (CSCs) from OSCC cell lines via a sphere-forming assay and the characterization of their stem cell-like features. (a) The morphology of the parental SAS and H103 and their derived tumour spheres. SAS and H103 in normal culture media were observed as polygonal squamous epithelial cells with the adherent growth pattern. Within 7 d, tumour spheres, comprised of aggregated and suspended cells derived from SAS and H103, were formed in the specialized serum-free medium containing serum substitute, heparin, and growth factors and in a low attachment plate (100× magnification). The average diameters of the SAS and H103 tumour spheres were 133.4 ± 34.36 µm and 68.1 ± 13.37 µm, respectively. (b) Assessment of cell viability of SAS, SAS tumour spheres, and H103 after 72 h exposure to cisplatin. IC50 was defined as the concentration of cisplatin required to reduce cell viability by half. Higher IC50 values indicated lower sensitivity of the cells towards cisplatin and possibly cisplatin resistance. (c) Western blots of Sox2, Oct4 and ß-actin and the relative expression levels of the Sox2 and Oct4 transcription factors normalized to the ß-actin protein in SAS and SAS tumour spheres. The full-length blots are presented in Supplementary Figure S2. (d) Expression of CD338, CD117 and CD44 surface markers in both SAS and SAS tumour spheres, as analyzed by flow cytometry. Multi-staining flow cytometry was used to analyse the surface expression of CD338 and CD117 for (I) SAS and (II) SAS tumour spheres. Single-staining flow cytometry was used to analyse the surface expression of CD44 for (III) SAS and (IV) SAS tumour spheres. All the data are presented as mean ± SD. **P < 0.01, n = 3.