Structure of the SALL4–RBBp4 Complex.

To target SALL4–NuRD interaction, we first determined the direct binding of SALL4(1–12) to RBBp4. We utilized the first 12 aa of SALL4 in isothermal titration calorimetry (ITC) assays to access the binding affinity of SALL4 to RBBp4, and found that the complex formed with a K_D of 1.04 ± 0.06 μM (Fig. 1A). These binding kinetics were further confirmed using surface plasmon resonance (SPR), with a calculated K_D for binding between the SALL4 peptide and RBBp4 of 1.5 μM (k_on = 16,830 ± 460 M⁻¹s⁻¹; k_off = 0.026 ± 0.00045 s⁻¹) (Fig. 1B).

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Fig. 1.

Structure of RBBp4–SALL4(1–12) complex and their binding affinity. (A) ITC profiles of SALL4 WT peptide titrated against RBBp4 are shown in raw (Upper) and a simulated curve in a 1:1 binding model (Lower). (B) Sensorgram of SPR demonstrated binding of SALL4 WT peptide to RBBp4 immobilized on a dextran-coated chip. (C) Front view of the RBBp4–SALL4(1–12) complex. RBBp4 is depicted in yellow, green (β-sheet), and red (α-helix), and the SALL4 peptide is depicted in blue. N and C termini of RBBp4 are labeled. (D) Diagram representing electrostatic potential. Acidic patches are indicated in red, neutral in white, and basic in blue. (E) The final 2F₀–F_c electron density map (contoured at 1σ) for the key residues of SALL4 peptide from Met1 to Ile-12. (F) Side chains of RBBP4 (green) interacting with SALL4 peptide (blue) is shown in stick representation. Unique interactions of SALL4–RBBp4 are shown in the boxes.

We next determined the crystal structure of the RBBp4–SALL4(1–12 aa) complex to obtain structural information of the SALL4–RBBp4 protein–protein interaction site. The complex was solved at 2.7-Å resolution (SI Appendix, Table S1). RBBp4 forms a seven-sheet β-propeller (residue 33–404) with an N-terminal α-helix (Fig. 1C). All 12 residues of the SALL4 peptide are well defined in the electron density map, with 9 of the residues making favorable interactions with RBBp4. The substrate binding site of RBBp4 is highly acidic, with eight glutamic acid and two aspartic acid residues within 5 Å of the SALL4 peptide. This negatively charged interface binds the predominantly positively charged SALL4 peptide, which has five basic residues: Arg3, Arg4, Lys5, Lys8, and His11 (Fig. 1 D and E). Arg3 and Lys5 of SALL4 form charged interactions with Glu275, Glu319, and with Glu126, Glu179, respectively, in RBBp4 (Fig. 1F and SI Appendix, Table S2). Arg4 forms a salt bridge with Glu231, whereas His11 makes π–cation interactions with Trp42. Several unique hydrogen bonding contacts were observed between Arg3:Lys376, Arg4:Phe321, Arg4:Arg129, and Pro9:Ser73 of the RBBp4–SALL4 complex (Fig. 1F and SI Appendix, Table S2). Additional hydrogen bonds between residues Ser2 to Gln6 and Gln10 to Ile12 stabilize the SALL4 peptide, and several hydrophobic interactions stabilize the complex. The Arg4 side chain is deeply buried into RBBp4 (buried surface area 211 Ų), whereas Lys5 and Pro9 bind in shallow grooves.

RRK Residues Are Crucial for RBBp4–SALL4 Interaction.

Structural analysis of the RBBp4–SALL4(1–12) complex revealed a large and shallow acidic interaction surface, suitable for developing a peptide inhibitor to block the interaction. In this regard, we undertook an integrated approach by combining computational studies with biophysical assays to determine the important amino acids for the SALL4–RBBp4 interaction. The structural analysis of the complex indicated that Arg3, Arg4, and Lys5 of SALL4 are crucial for binding. We confirmed this structural hypothesis using computational alanine scanning, and found that alanine substitutions of Arg3, Arg4, and Lys5 greatly affected the binding free energy (19, 16, and 14 kcal/mol, respectively) (Fig. 2A). Based on the in silico analysis, we subsequently performed a biochemical alanine scan of these residues with a series of mutant peptides using a fluorescence polarization assay (Fig. 2 B and C and SI Appendix, Fig. S1). Compared with the WT peptide (IC₅₀ = 1.0 µM), peptides bearing R3A, R4A, or K5A mutations demonstrated significantly decreased IC₅₀ values (4.5, 8.9, and 7 µM, respectively) (Fig. 2B), whereas the Q6A mutation had a minimal effect (IC₅₀ = 1.3 µM). Double mutations with two key residues, R3A,R4A; R4A,K5A; and R3A,K5A; abolished the interaction, with IC₅₀ values noted above 100 µM, whereas double mutants with the loss of only one key residue showed reduced but positive binding (IC₅₀ = 4.4 µM, 4.1 µM, and 4.7 µM, respectively) (Fig. 2B and SI Appendix, Fig. S1). These findings confirmed that Arg3, Arg4, and Lys5 are essential residues involved in the SALL4–RBBp4 interaction.

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Fig. 2.

Key residues involved in RBBp4–SALL4(1–12) binding. (A) Computational alanine scanning (CAS) was carried out on all 12 residues of the SALL4 peptide. The difference in the binding free energy (ΔΔG_bind) of the alanine mutants (ΔG_mutant) and WT (ΔG_{wild type}) was calculated (ΔΔG_bind = ΔG_mutant − ΔG_{wild type}). ΔΔG_bind was tabulated (Left) and plotted in a bar chart (Right). (B) Alignment of mutant peptides. Mutated residues are highlighted in red. The IC₅₀ of each peptide, including WT, was determined by fluorescence polarization. Different concentrations of each peptide were titrated into a mixture of 0.045 μM RBBp4 and 0.1 μM of C-labeled FITC-SALL4 WT peptide. Polarization was measured in millipolarization. (C) Representative IC₅₀ curves of SALL4 WT and double-mutant MUT R3A,K5A by fluorescence polarization. (D) Cell viability assays were performed on SNU398 cells treated with SALL4 WT or MUT R3A,K5A peptides. Pep-1 carrier was added to the peptide to facilitate cellular penetration of the peptides. (E) Cells were treated with 8 mM of peptides with Pep-1 carrier for 24 h, and transcript levels of the SALL4–RBBp4 downstream gene, PTEN, were measured using quantitative real-time PCR. Data represent mean ± SD (n = 3). N.S., not significant.

We next selected a representative double mutant of essential residues (MSARAQAKPQHI; MUT R3A,K5A) and compared its effect with the WT peptide on cell viability in SNU398 HCC cells, which express high levels of SALL4 RNA and protein (16). While the WT peptide exerted an inhibitory effect on cell number, the MUT peptide did not (Fig. 2D). Further qPCR analysis revealed a threefold increase in PTEN expression (P < 0.0001) in cells treated with the WT peptide compared with untreated cells, whereas MUT-treated cells again showed no significant change (P value not significant) (Fig. 2E). These findings indicate that the MUT peptide could not block the RBBp4–SALL4 interaction and failed to release the suppressive complex from the PTEN promoter, unlike its WT counterpart.

Optimization of a Candidate Therapeutic Peptide.

After determining the key interactions between RBBp4 and SALL4(1–12), and by using structural data of the RBBp4–SALL4(1–12) complex as a platform, we then undertook a peptide substrate-based approach to design and optimize a potent inhibitor of the SALL4–RBBp4 interaction. We first determined the minimum length required for bioactivity through a truncation analysis of the WT peptide (SI Appendix, Table S3, peptide 1). Removing the first two N-terminal residues, Met and Ser (SI Appendix, Table S3, peptides 2 and 3), increased the peptide binding affinity to RBBp4 compared with the WT (IC₅₀ = 0.60 and 0.36 vs. 1.0 μM, respectively); yet C-terminal truncations resulted in a marginal loss of binding affinity (SI Appendix, Table S3) (IC₅₀ = 1.29, 0.80, and 1.91 μM for peptides 5, 6, and 7, respectively). Removal of a key binding residue (peptide 4) abolished the binding affinity (IC₅₀ > 20 μM). To further improve binding potency, peptide 3 was selected as the sequence template and subjected to a systematic single-residue mutation analysis with alanine substitutions. Substituting the nonessential residues of peptide 3 with Ala (SI Appendix, Table S3, peptides 11–16) yielded more potent peptides, whereas substituting the essential residues of peptide 3 with Ala abolished binding (SI Appendix, Table S3, peptides 8–10). This suggests that nonessential residues of peptide 3 could be replaced with other amino acid residues for sequence optimization. Systematic substitution of the nonessential residues (SI Appendix, Table S3, peptide 20–45) revealed a marked reduction of IC₅₀ upon replacement of Gln-4, Pro-7, and His-9 of peptide 3. Gln4 sits in a small binding pocket formed by Pro43, His71, and Glu395 of RBBp4, which is able to accommodate amino acid residues with hydrophobic side chains. Consequently, substituting Gln4 with Leu or Phe (peptides 23 and 24) led to improved binding affinities, particularly Phe, which induced a sevenfold enhancement in binding affinity over that of peptide 3 (IC₅₀ 0.05 vs. 0.36 μM) (SI Appendix, Table S3). Additionally, a Phe substitution (peptide 34) for Pro7 further increased the potency of the peptide (IC₅₀ 0.17 vs. 0.36 μM) (SI Appendix, Table S3). Using computer modeling, the aromatic ring of Phe7 was found to be solvent-exposed and not involved in RBBp4 binding. However, its backbone amide proton could be involved in H-bonding to the side-chain carboxyl moiety of Glu395, an interaction lacking in Pro7 (SI Appendix, Fig. S2). In an effort to enhance the π–π interaction to RBBp4, His9 was replaced by aromatic residues Trp (peptide 41), and the substitution improved the binding affinity by threefold compared with that of peptide 3 (IC₅₀ 0.12 vs. 0.36 μM) (SI Appendix, Table S3).

These three substitutions (Gln4Phe, Pro7Phe, and His9Trp) were incorporated into peptide 46 (RRKFAKFQWI, named FFW hereafter). Fluorescence polarization assay confirmed the high potency of FFW, with a >43-fold increase in affinity compared with the original 12-residue WT peptide (IC₅₀ = 0.023 vs. 1.0 μM) (SI Appendix, Fig. S3 and Table S1).

FFW Reverse-Transcription Repression by SALL4–RBBp4.

To elucidate the regulatory pathways that FFW could affect, a penetratin sequence (PEN) was attached to the N terminus of FFW to facilitate penetration into cells in culture (Fig. 3A). The FFW peptide is a highly basic and hydrophobic molecule. To test the ability of FFW to penetrate cells without the penetratin sequence, we treated both peptides to SNU398 cells and MTT assays were conducted after 72 h of incubation. The results demonstrated that although FFW is hydrophobic, the FFW peptide did not show any effect on cell viability without the conjugation of the penetratin sequence (Fig. 3B). We have also conjugated FITC to the amino terminus of FFW and subjected it to fluorescence microscopy, but could not detect any uptake of the peptide by the cells (SI Appendix, Fig. S4).

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Fig. 3.

Transcriptome profiling of the PEN-, PEN-MUT–, PEN-WT–, and PEN-FFW–treated SNU398 cells. (A) The penetratin sequence was added to WT, MUT, and FFW peptides to aid cellular penetration. (B) SNU398 were treated with FFW without the penetratin sequence (FFW), or FFW conjugated with the penetratin sequence (PEN-FFW), and subjected to a cell viability assay (MTT) after 72 h. TSA (Trichostatin A) was used as positive control. DMSO was included as vehicle control. (C) SALL4 was immunoprecipitated from SNU-398 nuclear extracts (1 × 10⁶ cells) pretreated with DMSO, PEN-FFW (30 µM), or PEN-MUT (30 µM) for 4 h. Immunoprecipitates were analyzed by Western blot using SALL4, RBBp4, and HDAC1 antibodies. SALL4–RBBp4/NuRD interaction was abrogated by PEN-FFW treatment. (D) Hierarchical clustering based on whole transcriptome profiling, demonstrating that PEN-FFW distinctly clustered away from PEN, PEN-MUT, and PEN-WT. (E) Heatmap presentation of the DEGs encoding cell adhesion molecules, tumor suppressors, and apoptosis-related transcripts. (F) M-A (log-average fold-changes versus logarithmic mean intensity) plot of PEN-FFW over the control PEN demonstrating that significantly changed genes are almost all up-regulated. (G) GSEA in PEN-FFW versus the controls (PEN and PEN-MUT) using the whole transcriptome of the samples.

In addition to PEN-FFW, the PEN sequence was also conjugated to WT and MUT peptides. To test if the PEN-FFW peptide could disrupt endogenous SALL4–NuRD interaction, we performed coimmunoprecipitation after peptide treatment using SALL4 antibody (Fig. 3C). We found that the endogenous SALL4–RBBp4/HDAC/NuRD interaction was abrogated after PEN-FFW treatment, but not the controls. We next sequenced RNA transcripts (RNA-seq) from SNU398 cells treated with PEN alone, and different PEN conjugated peptides (30 µM, 8 h). Unbiased hierarchical clustering of the whole transcriptome data revealed that the PEN-FFW–treated sample was distinctly clustered away from the rest of the samples (Fig. 3D), whereas PEN- and PEN-MUT–treated samples (controls) were closely clustered together with similar transcriptome profiling, and the PEN-WT–treated sample was clustered in between. Strikingly, heatmap presentation of differentially expressed genes (DEGs) demonstrated that PEN-FFW treatment induced almost exclusively gene activation, in which 99.5% of the PEN-FFW DEGs were up-regulated (575 transcripts) and only 0.5% of the DEGs (three transcripts) were down-regulated (Fig. 3E and Dataset S1). This indicate that the PEN-FFW treatment had reversed the repressive function of SALL4, switching it from a dual-action transcription factor to a single-activator mode. This observation was further confirmed by M-A plot (log fold-change versus log mean intensity) of PEN-FFW versus controls (Fig. 3F), in which a majority of the DEGs are up-regulated.

Next, gene set enrichment analysis (GSEA) was performed using the whole transcriptome between PEN-FFW or PEN-WT and the two negative controls (PEN and PEN-MUT), respectively. GSEA analysis revealed a significant concordance between genes up-regulated in cells treated with PEN-FFW and genes down-regulated by overexpressing oncogenes like KRAS and ALK (Fig. 3G and Datasets S2 and S3). Genes down-regulated in HCC, for example ATP1A2 and LCN8, were also specifically up-regulated in PEN-FFW–treated samples, while further analysis showed that targets of HNF4a, a key liver transcription factor, were also enriched in PEN-FFW–treated cells. Interestingly, PEN-FFW–enriched genes were associated with the repressive H3K27Me3 mark before peptide treatment, indicating these transcripts had undergone epigenetic modulation following disruption of the SALL4–NuRD interaction. (Fig. 3G and Dataset S3).

SALL4–RBBp4 Disruption Induced Apoptosis and Enhanced Cell Adhesion.

Next, we conducted chromatin immunoprecipitation coupled with next-generation sequencing (ChIP-seq) on SNU398 cells to detect the SALL4 binding regions in the genome to compare with the PEN-FFW DEGs. Of the 7,883 SALL4 binding peaks, 60% are located at promoter regions, with H3K27Ac marks enriched around the SALL4 peaks (Fig. 4A). Interestingly, 57 of the 575 PEN-FFW DEGs have strong SALL4 binding peaks within 2 kb of the transcription start sites, suggesting that these transcripts are direct targets of the SALL4–RBBp4/NuRD interaction (Fig. 4B). Furthermore, we observed that chromatin remodelers and transcripts encoding molecules that facilitate transcription activation are among the highest expressed DEGs of these 57 transcripts (Fig. 4C). These include: POLR2A, the largest subunit of POLII; pre-mRNA splicing factor SRRM2; and chromatin remodeling protein SRCAP. Interestingly, both of the H3K4-specific methytransferases, MLL2 and SETD1B, also demonstrate promoter occupancy by SALL4 (Fig. 4D) and up-regulation after SALL4–RBBp4/NuRD disruption, implying that the SALL4–RBBp4/NuRD complex strongly regulates chromatin status.

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Fig. 4.

Enhanced apoptosis and cell–cell adhesion by PEN-FFW treatment. (A) Heatmap representing the occupancy of SALL4 in the human genome. SALL4 binding loci were enclosed by histones marked with H3K27Ac. The number indicates fold-change after scaling the ChIP-seq signal to 1× coverage of the genome. (B) Venn diagram showing the overlap between the SALL4A ChIP-seq peaks and PEN-FFW DEGs in SNU398 cells. (C) RNA expression value of the 57 overlapped transcripts showed a group of transcription modelers were highly enriched. (D) Genome browser tracks of the ChIP-Seq representing the occupancy of SALL4 at three representative promoters. (E) Gene Ontology analysis revealed pathways altered in the PEN-FFW–treated cells under the control of SALL4–NuRD. (F) Annexin V/PI apoptosis assay were performed with PEN- (30 µM) and PEN-FFW– (30 µM) treated (i) SNU398, (ii) Huh7, and (iii) Hep3B cells, after 24 h of peptide incubation. Apoptotic populations were accessed by flow cytometry and from Annexin V⁺ quadrants. (G) Transwell migration assay using PEN- (1 0 μM) and PEN-FFW– (10 μM) treated SNU398, Huh7, and Hep3B cells. (H) Wound-healing assay using SNU398 cells after low concentration (10 μM) treatment of different peptides for 3 d. Images of the cells were captured on day 0 and day 3 after peptide treatment. On day 0, the clear space created by the scratch was marked with red dotted vertical lines. On day 3, any remaining clear space was marked by the red dotted vertical lines, with no marking if the space was fully invaded by adjacent cells.

A significant proportion of the PEN-FFW DEGs are miRNA and noncoding RNAs (23% of the transcriptome). We focused on annotated transcripts and performed pathway analysis for these transcripts. Intracellular Ca²⁺ concentration is tightly regulated in cells. An unexpected finding of the pathway analysis revealed that a group of transcripts involved in calcium signaling, such as calmodulin (CALML6) and GRIN1, are up-regulated (Fig. 4E), suggesting that SALL4–RBBp4 disruption might induce a Ca²⁺ influx in PEN-FFW–treated cells. Because Ca²⁺ could act as a secondary messenger to activate apoptosis (23), we detected transcripts encoding molecules involved in the apoptosis pathway, such as CARD14, RAPSN, CHRNG, and BCL2L14, in the PEN-FFW DEGs. To further investigate the effect of these gene changes, three liver cancer cell lines with high expression of SALL4, SNU398, Huh7, and Hep3B (16) were treated with different peptides for 6 h (SI Appendix, Fig. S5) or 24 h (Fig. 4F). The cells were stained with propidium iodide (PI) and anti-Annexin V antibody to assess the apoptotic cell population by flow cytometry. After 24 h, PEN-FFW treatment significantly increased the apoptotic population (PI⁺/Annexin V⁺, Annexin V⁺) from 16.6% in PEN control to 32.5% after PEN-FFW treatment in SNU398 (Fig. 4 F, i); from 14.3% in PEN control to 73.5% in PEN-FFW treated Huh7 cells (Fig. 4 F, ii); and from 13.5% in PEN control to 51.7% in PEN-FFW treated Hep3B cells (Fig. 4 F, iii), supporting previous data from transcriptome analysis.

Loss of cell–cell or cell–extracellular matrix (ECM) contact is often observed in cancer as transformed cells gain motility and invasiveness. In contrast, gain of cell–cell and cell–ECM contact could inhibit cancer cell growth and prevent metastasis. In our transcriptome analysis, the most distinct cellular pathway associated with PEN-FFW DEGs were transcripts encoding molecules involved in cell–cell adhesion and ECM interactions, including CDH4, Claudin-5, -18, and -20, collagen (COL4A4, COL5A1), integrin (ITGA10), laminin (LAMA5), and vitronectin (VTN). Furthermore, a group of cadherins were also up-regulated (CDH4, FAT2, PCDH12, PCDHAG12) after PEN-FFW treatment. We therefore hypothesize that the disruption of SALL4–RBBp4 could tighten cell–cell contacts and limit mobility of these cells. To examine this hypothesis, we performed a cell-invasion assay in Boyden chambers in which serum-starved SNU398, Huh7, or Hep3B cells were treated with different peptides (10 µM). Cells migrating toward 10% serum and invading the membrane pores after 24 h were stained with DAPI, and quantified by counting cells per microscope field-of-view. Compared with PEN- and PEN-MUT–treated cells, cell migration ability was indeed markedly impaired in PEN-FFW–treated cells. For both SNU398 and Huh7, more than an 85% reduction of migrated cells was observed in the PEN-FFW–treated group, compared with PEN (Fig. 4G) (P < 0.001 and P < 0.0001, respectively). For Hep3B, the migration activity is low compared with the other two cell lines, in which only 44 cells were found to have passed the membrane after PEN treatment, and this number dwindled to 14 cells after PEN-FFW treatment. Wound-healing assays were also performed to assess the migration activity of PEN-FFW–treated cells. We found that PEN-FFW–treated cells had slower migration activity compared with PEN-MUT and PEN controls in SNU398 (Fig. 4H), Huh7, and Hep3B cells (SI Appendix, Fig. S6).

Beside the pathways mentioned previously, a class of tumor suppressor genes was also restored after PEN-FFW treatment (Fig. 4E). TSC1/2, which inhibits mTORC1 (24), was enriched 2.5-fold after PEN-FFW treatment (Dataset S1). Another example, LRRC4, which functions to delay cell cycle progression (25), was increased after PEN-FFW treatment. A negative regulator of RAS, DOK3, was also found up-regulated in the PEN-FFW treated cells. Taken together, our data suggest that the disruption of the SALL4–RBBp4 interaction by the PEN-FFW peptide could lead to up-regulation of cell adhesion molecules to suppress migration, Ca²⁺ influx to induce apoptosis, and a group of tumor suppressors that oppose various oncogenic processes.

Prognostic Value of PEN-FFW Up-Regulated Genes.

Because PEN-FFW treatment leads to significant apoptosis of SNU398 liver cancer cells (Fig. 4F) and dramatic inhibition of xenograft tumor growth (as presented below; see also Fig. 6), we were interested in evaluating the potential prognostic value of these PEN-FFW up-regulated DEGs in patients. Thus, we first overlapped these up-regulated genes with genes that are significantly up-regulated in normal liver samples compared with liver cancer patients in three independent cohorts (Fig. 5A, schematic representative of the analysis). Across the three cohorts, 26 of these PEN-FFW up-regulated DEGs show consistent overexpression in adjacent nontumor samples compared with the tumor (Fig. 5B and Dataset S4). We next explored their diagnostic abilities in separating HCC samples from normal tissues using the receiver operator curve (ROC), and were able to identify nine of them with consistently high area under curve across all three cohorts (Dataset S5). Three examples of these genes (IGFALS, GNAO1, and ECM1) are depicted in Fig. 5C.

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Fig. 5.

PEN-FFW DEGs predicted favorable outcome for HCC patients. (A) Schematic representation of the integrated analysis of treatment data with patient data for selection of PEN-FFW up-regulated genes having both diagnostic and prognostic values. (B) Heatmap showing 26 genes with consistent up-regulation in adjacent nontumor tissue compared with liver tumor samples across three independent cohorts (TCGA-LIHC, GSE64041, and GSE76427). (C) ROC performance of three genes (IGFALS, GNAO1, and ECM1) as examples for the further selection of the 26 genes for separation of tumor samples from adjacent nontumor tissue across three independent cohorts. (D) Kaplan–Meier analysis of IGFALS, SLC22A1, ASPG, and FTCD in further selection of the 26 genes for favorable survival across two independent cohorts (TCGA-LIHC, Right; GSE54236, Left).

Concomitantly, to further evaluate the prognostic relevance of these 26 PEN-FFW up-regulated DEGs, we examined their survival differences in two independent HCC cohorts. We were able to identify eight genes with favorable survival difference for the patients with high expression compared with those with low expression (Fig. 5A and Dataset S6). By overlapping the two gene sets from ROC and survival analysis, we were able to identify four PEN-FFW up-regulated DEGs having both high diagnostic and high prognostic values, and they are IGFALS, SLC22A1, ASPG, and FTCD. The favorable survival difference from these four genes is depicted in Fig. 5D, using two independent cohorts. The prognostic value and diagnostic value of these four genes are highlighted in bold in Datasets S5 and S6.

Therapeutic Peptide FFW Leads to Tumor Regression in Xenograft Models.

Having developed the highly potent FFW peptide affecting SALL4 transcription, we next compared its efficacy to WT and mutant peptides at the cellular level. SNU398 cells were treated with PEN-MUT, PEN-WT, and PEN-FFW for 72 h with a series of concentrations, and cell viability was measured with the MTT assay. We observed that PEN-FFW conferred a 4-fold improvement in reducing cell viability compared with the PEN-WT (Fig. 6A) (EC₅₀ 7.6 μM vs. 30 μM, respectively), and more than 13-fold compared with PEN-MUT (EC₅₀ > 100 μM). To further confirm the specific therapeutic effect of PEN-FFW in SALL4-expressing HCC cells, we employed SNU398, Huh7, and Hep3B, three HCC lines with high levels of SALL4 (16); SNU387, a HCC line with undetectable levels of SALL4; and THLE-2 and THLE-3, immortalized normal liver epithelial cell lines with undetectable levels of SALL4, and treated these cells with PEN-MUT, PEN-WT, or PEN-FFW peptides (SI Appendix, Fig. S7). Our data demonstrate the specificity of PEN-FFW in targeting SALL4-high HCC cells (SNU398, Huh7, and Hep3B), and not SALL4-low HCC cells (SNU387) or immortalized normal liver epithelial cell lines THLE-2 and THLE-3, highlighting a clear therapeutic window for treatment.

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Fig. 6.

Antitumor activity of the candidate therapeutic peptide FFW. (A) Penetratin-conjugated peptides were subjected to the cell viability assay in SNU398 cells, demonstrating the high potency of PEN-FFW. TSA (Trichostatin A) was used as positive control to reduce cell viability. (B) 7.2 × 10⁵ SNU398 cells were inoculated subcutaneously into the right flank of NSG mice. Tumors grew for 1 wk before peptide treatment was administered on alternate days for a total of five injections. (C) Tumor growth was observed and charted using tumor volume vs. time. Data represent mean ± SD (n = 5). (D) Relative tumor size on day 17. (E) Tumor weight of mice from C (n = 5 per group): PEN-FFW, μ = 88.34 mg; PEN, 1,550.78 mg; PEN-MUT, 1,273.46 mg; PEN-WT, 563.46 mg. Data represent mean ± SD (n = 5). The experiments were performed twice independently; representative data from a single experiment are shown. (F) NSG mice were inoculated with 1 × 10⁶ PLC8024 cells. Vehicle control, Sorafenib (20 mg/kg), PEN-FFW (30 mg/kg), and combination of Sorafenib (20 mg/kg) and PEN-FFW (30 mg/kg) were administered when xenografts reached 70–100 mm³ (n = 6 per group). Tumor growth was observed and charted using tumor volume vs. time. The experiments were performed twice independently; representative data from a single experiment are shown.

To further test the therapeutic effect of PEN-FFW in vivo, SNU398 cells were implanted subcutaneously into the flanks of NOD/SCID/γ-mice (NSG), and the mice were randomly grouped for peptide treatments (n = 5 per group) (Fig. 6B). For mice treated with PEN (control) or PEN-MUT, tumors progressively increased in size, showing that neither peptide was able to inhibit tumor growth (Fig. 6C). In contrast, although PEN-WT impaired tumor growth (P = 0.001), PEN-FFW induced a much stronger therapeutic effect (P = 0.0008) with a tumor growth inhibition of 85%. PEN-FFW–treated mice also displayed the smallest tumors (Fig. 6D), with significantly lower tumor weight (μ = 88 mg in PEN-FFW, μ = 564 mg in PEN-WT, and μ = 1,550 mg in PEN control) (Fig. 6E). To access toxicity, we tabulated the body weight of the mice at end point (SI Appendix, Fig. S8) and also traced the body weight change throughout the experiment, and found no significant difference, suggesting the overall well-being of the mice receiving the peptide treatments.

To benchmark against current therapy used in advanced stage HCC, we compared PEN-FFW–treated SNU398 tumor xenografts to that of Sorafenib-treated xenografts in a separate set of experiments (SI Appendix, Fig. S9) (n = 6 per treatment group). Interestingly, PEN-FFW treatment resulted in stronger antitumor activity than Sorafenib compared with vehicle-treated groups, albeit not statistically significant. Furthermore, mice treated with PEN-FFW in combination with Sorafenib showed the slowest rate of tumor growth. These data suggest a potential therapeutic effect of PEN-FFW in treating HCC patients, including those refractory to Sorafenib treatment. To further test this hypothesis, we developed a second xenograft model with a chemo-resistant HCC cell line, PLC8024, which is both SALL4⁺ and CD133⁺, and also radio-resistant (26, 27) (n = 6 per treatment group). In this chemo-resistant model, we observed greater tumor growth (+1.5-fold) in the Sorafenib-treated group compared with the vehicle control group (Fig. 6F). Although PEN-FFW treatment showed minimal tumor inhibitory effect in this model, a significant synergistic effect of Sorafenib and PEN-FFW was observed in mice treated with both agents (P = 0.02, tumor growth inhibition 57% and 73% compared with control and sorafenib treated group, respectively) (Fig. 6F). This result further suggests that PEN-FFW alone, or as part of combination therapy, could bring clinical benefits to advanced stage HCC patients to overcome resistance to Sorafenib.

Drug-Like Properties of FFW.

Biologics or compounds rapidly degraded in plasma generally demonstrate little efficacy in vivo. To further evaluate the potential of further development of PEN-FFW as a drug candidate, we examined the plasma stability, cell-penetration kinetics, and toxicity of the peptide. First, we monitored the degradation of PEN-FFW (1 µM) in de-identified, healthy human plasma by LC-MS/MS. At 30-min incubation (Fig. 7A, Inset), more than 90% of the peptide remained in the plasma. In comparison, the compound Eucatropine as a control was rapidly degraded to 40% (SI Appendix, Fig. S10, Inset). Extending the experiment duration by 24 h revealed more than 50% of the peptide remained intact in the plasma after 4 h, gradually decreasing to ∼20% on the 24th hour (Fig. 7A). This suggests that PEN-FFW can potentially be developed as an intravenous drug. We subsequently conjugated FITC to the N terminus of PEN-FFW to assess the permeability and stability of the peptide in cells. Live cell imaging was performed on the treated cells at 2-min intervals for the first hour, and at 5-min intervals for the subsequent 23 h. It was observed that FITC-PEN-FFW entered cells by 18 min, and translocated to the nucleus by 22 min. At 2.5 h, FITC-PEN-FFW had entered every cell in the microscopic field, with incremental FITC-signals at 24 h (Fig. 7B and Movie S1).

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Fig. 7.

Drug-like properties of PEN-FFW. (A) The PEN-FFW peptide was incubated with human plasma to test for stability. Samples were subjected to LC-MS/MS measurement at 0, 5, 10, 15, and 30 min (Inset); and subsequently at 0, 1, 2, 4, and 24 h. (B) SNU398 cells were labeled with Hoechst 33342 for 5 min, and FITC-PEN-FFW was added to the media at 10 μM. Live cell imaging was performed with images taken at every 2 min for the first hour, and at 5-min intervals for the subsequent 23 h. Montages at 0, 2.5, and 24 h are shown. (Scale bars, 5 μm.) (C) Four C57BL/6 mice were exposed to vehicle or peptide treatment every alternate day for a total of 17 d. Serial body weights and end-point body weights of the mice are shown. (D) Serum AST and ALT of the mice were measured after a 10-d wash-out period after peptide treatment. No significant change between the two groups was observed. N.S., not significant. (E) Blood counts of the mice were performed at end point. (F) Representative microphotographs from the major organs (heart, liver, lung, spleen, stomach) harvested from vehicle control and PEN-FFW–treated animals are shown. The tissue sections were examined by a qualified pathologist. (Scale bars, 200 μm.)

Finally, potential toxic effects of the peptide were assessed with C57BL/6 mice harboring an intact immune system (n = 4). The mice were exposed to intraperitoneal administration of PEN-FFW (30 mg/kg) or vehicle (10% DMSO) every alternate day over the course of 17 d to a cumulative dose of 270 mg/kg. Mice in both groups remained alert, responsive, and did not exhibit notable signs of toxicity, such as lethargy, loss of mobility, or weight loss (Fig. 7C). After a 7-d washout period, complete blood counts and liver-function assay tests were performed, and organs were harvested for histology. To access potential liver injury caused by the peptide treatment, serum AST (aspartate aminotransferase) and ALT (alanine aminotransferase) levels were tested. Elevation of the two enzymes was not observed in the treatment group (Fig. 7D), indicating no liver damage was detected following treatment. Concurrently, no significant change in blood counts (Fig. 7E) or tissue damage (Fig. 7F) was observed in the treatment group compared with the control group.