Peptide‑Based Therapeutics Targeting the SLC39A14‑PIWIL2 Fusion in Hepatocellular Carcinoma

Peptide‑Based Therapeutics Targeting the SLC39A14‑PIWIL2 Fusion in Hepatocellular Carcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Peptide‑Based Therapeutics Targeting the SLC39A14‑PIWIL2 Fusion in Hepatocellular Carcinoma Masaud Shah, Sung Ung Moon, Ji-Hye Choi, Min Jae Kim, Hyun Goo Woo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7217926/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Fusion genes are key oncogenic drivers in various cancers, yet their role in hepatocellular carcinoma (HCC) remains underexplored. To identify fusion genes contributing to HCC progression, we analyzed RNA-seq data from HCC patients and identified SLC39A14-PIWIL2 as a novel putative driver. Functional assays revealed that the SLC39A14 promoter induces overexpression of a truncated PIWIL2 protein (tPIWIL2), which retains oncogenic MID and PIWI domains. Expression of tPIWIL2 promotes aggressive tumor progression by interacting with oncogenic partners HDAC3 and NME2, as demonstrated through structural modeling and molecular dynamics simulations. To disrupt these interactions, we designed novel decoy peptides that competitively bind PIWIL2 at the HDAC3 and NME2 interfaces, effectively inhibiting tPIWIL2-driven tumor activity in multiple HCC cell lines. Among them, the NEP1 peptide substantially suppressed oncogenic interactions, and its co-administration with 5-Fluorouracil reduced PIWIL2-induced chemoresistance, enhancing therapeutic efficacy. These findings establish SLC39A14-PIWIL2 as a novel oncogenic fusion in HCC and propose fusion protein-targeted peptide therapeutics as a promising strategy for precision treatment in HCC patients. Fusion gene HCC PIWIL2 SLC39A14 Therapeutics-peptides Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Molecular and genetic complexity of Hepatocellular Carcinoma (HCC) impedes early diagnosis and limits treatment efficacy, thereby contributing to poor survival outcomes [1]. Advances in high-throughput genomic sequencing have unraveled the intricate molecular prerequisites of HCC, revealing its molecular heterogeneity with aberrations across various pathways, including inflammation, cell cycle control, invasion, metabolism, and metastasis [2–4]. In addition, chromosomal rearrangements and fusion genes stand out as critical oncogenic drivers across multiple cancer types [5–8]. These fusion genes serve as diagnostic biomarkers, such as ERG and ETV1, others like ALK, RET, BRAF, and FGFR1-4 offer actionable therapeutic targets [9, 10]. In HCC, a limited number of fusion genes have been now identified with potential implications in tumor progression and prognosis. The DNAJB1-PRKACA fusion serves as a driver mutation in fibrolamellar carcinoma, a subtype of HCC [11]. The LINE1-MET fusion has also been highlighted in HCC development [12]. Furthermore, fusions such as SLC45A2-AMACR, ITCH-ASIP, and RNF138-RNF125 have been associated with better HCC prognoses, while MAN2A1-FER, CCNH-C5orf30, and SLC45A2-AMACR, detectable in serum, show potential for HCC diagnosis [13]. In this study, we identified a novel SLC39A14-PIWIL2 fusion gene in HCC patients’ samples. This fusion was formed by chromosomal inversion, joining SLC39A14 exon 1 with PIWIL2 exons 7–23 and resulting in the upregulation of PIWIL2 and promoting HCC progression. Additionally, structural modeling of PIWIL2 interactions with downstream proteins, alongside the design of PIWIL2 inhibitory peptides, has further highlighted its potential as a therapeutic target in HCC, opening avenues for the development of PIWIL2-focused treatments. Materials and methods Identification of fusion transcripts from RNA-Seq data of HCC patient samples We identified the expression of fusion transcripts from our previously published RNA-seq data (68 HCC and 10 non-tumor tissues; GSE113617) [14]. By applying three different methods of SOAPfuse [15], ChimeraScan [16], and TopHat-Fusion [17] with default parameters and filtering out transcripts with fewer than 30 reads at the breakpoints, we could identify 14 fusion transcripts which were detected at least two of the methods. Human cancer cell lines, anticancer drug, and plasmids The SNU398 (purchased from the Korean Cell Line Bank, Seoul, Republic of Korea (KCLB) Cat# 00398_SNU-398, RRID: CVCL_0077), SNU449 (KCLB Cat# 00449_SNU-449, RRID: CVCL_0454), HepG2 (KCLB Cat# 88065_HepG2, RRID: CVCL_0027), and Huh7 (KCLB Cat# 60104_Huh7, RRID: CVCL_0336) cell lines were cultured in DMEM, MEM, or RPMI1640 (Gibco BRL, Grand Island, NY) supplemented with 10% FBS and 1% antibiotics at 37°C in a 5% CO2 incubator. PIWIL2, tPIWIL2, and SLC39A14-PIWIL2 constructs were cloned into PCDNA3.1 (RRID: Addgene_70219) or C-terminal 3xFLAG-tagged PCDNA3.1 (RRID: Addgene_208616) using the In-Fusion cloning method (Clontech, Mountain View, CA). PCR products were amplified with CloneAmp HiFi PCR Premix (TAKARA, Tokyo, Japan) and specific primers ( Table S1 ), followed by insertion into PCDNA3.1 using HindIII and ApaI. Constructs were confirmed by Sanger sequencing (Macrogen, Seoul, South Korea). The plasmids were transfected into the liver cancer cell lines (2 × 10⁶ cells per 60-mm dish) using 6 µg of Lipofectamine 3000 (Invitrogen, Thermo Fisher Scientific, Inc.), and incubated for 48 hours at 37°C in a CO₂ incubator. The cells were treated with various concentrations of 5-FU and peptides (0, 1, 2, 2.5, 5, 10, 12.5, 25, and 50 µM) for 4 days in media supplemented with 10% FBS. Immunoblotting (western blotting) Cells were harvested and lysed using lysis buffer (REF87787, Thermo Fisher Scientific), then centrifuged at ~ 13,000 ×g for 10 min at 4°C. Protein concentrations were determined with a Bradford protein assay kit (#5000006, Bio-Rad, Hercules, CA, USA). Equal amounts (30 µg) of protein were separated using 10% SDS-PAGE (Bio-Rad) and transferred to nitrocellulose membranes (#1620115, Bio-Rad) for immunoblotting. Membranes were washed three times with PBS (Welgene, Gyeongsangbuk-do, Republic of Korea) containing 0.1% Tween 20 (PBST; Sigma-Aldrich), blocked with PBST containing 1% bovine serum albumin (BSA, Bovogen, Melbourne, Australia) for 1 h at room temperature, and incubated with primary antibodies in PBST with 1% BSA overnight at 4°C. After washing, membranes were incubated with secondary antibodies (1:1000 dilution) against goat anti-rabbit IgG-HRP (Cell Signaling Technology Cat# 7074S, RRID: AB_2099233) or anti-mouse IgG-HRP (Cell Signaling Technology Cat# 7076S, RRID: AB_330924) for 1 h at room temperature and washed again. Membranes were developed with ECL Buffer (REF34580, Thermo Fisher Scientific) and images captured using an iBright 1500 imaging system (REF34580, Thermo Fisher Scientific). The following antibodies were used: FLAG (1:1000, Sigma-Aldrich, Cat# F1804, RRID: AB_262044), CTNNB1 (1:1000, Santa Cruz Biotechnology, Cat# sc-7963, RRID: AB_626807), c-myc (1:1000, Cell Signaling Technology, Cat# 9402, RRID: AB_2151827), p-Akt (1:1000, Cell Signaling Technology Cat# 4060S, RRID:AB_2315049), p-GSK-3β (1:1000, Cell Signaling Technology, Cat# 9336S, RRID: AB_331405), p-STAT3 (1:1000, Cell Signaling Technology, Cat# 9145S, RRID: AB_2491009), β-actin (1:2000, Santa Cruz Biotechnology, Cat# sc-47778, RRID:AB_626632), and GAPDH (1:5000, Abcam Cat# ab8245, RRID: AB_2107448). Immunocytochemistry analysis To examine c-myc localization, PIWIL2-overexpressing liver cancer cells were incubated with or without NEP1 peptide, fixed with 4% paraformaldehyde, and permeabilized with 0.25% Triton X-100. After washing, cells were blocked with 1% BSA and 0.1% Tween 20 for 1 h, then treated with primary antibodies against c-myc (1:100, Cell Signaling Technology, Cat# 9402, RRID: AB_2151827) and PIWIL2 (1:100, Abnova, Cat# MAB0843, RRID: AB_1204794) at 4°C for 24 h. Following primary antibody incubation, cells were incubated with Alexa Fluor 594-conjugated donkey anti-rabbit IgG (1:200, Molecular Probes Cat# A-21207, RRID: AB_141637) and Alexa Fluor 488-conjugated donkey anti-mouse IgG (1:200, Molecular Probes Cat# A-21202, RRID: AB_141607) secondary antibodies for 2 h at room temperature. Nuclei were stained with DAPI-containing mounting solution, and cells were visualized under an Axiovert 200 fluorescence microscope (Carl Zeiss). RT-quantitative PCR analysis Total RNA was isolated using RNeay (Qiagen, Hilden, Germany) for RT-qPCR analysis of target genes. RT-qPCR was performed using the iQ SYBR Green supermix (Bio-Rad, CA, USA) and the CFX96™ Real-Time system (Bio-Rad, Singapore). Reverse transcription was performed using TOPscript™ RT DryMIX (Enzynomics, Daejeon, Republic of Korea). The relative amounts of target genes were normalized to those of glyceraldehyde-3-phosphate dehydrogenase (GAPDH). The primer sets used are listed in table S1 in supplementary data. The 2 −ΔΔCq method was adopted to determine the fold changes (control vs. sample). Cell viability, spheroid formation, migration and invasion assay For phenotypic changes due to PIWIL2 overexpression, cells were seeded in 96-well plates (2×10³ cells/well) and incubated overnight at 37°C with 5% CO₂. After transfection, 5 mg/mL MTT solution was added and incubated for 2 h. The blue precipitate was dissolved in 150 µl DMSO, and absorbance at 550 nm was measured using a microplate reader. All experiments were done in triplicate. For colony formation, cells were transfected for 48 h, then seeded at 500 cells/well in 6-well plates and incubated for 14 days. Colonies were washed, fixed with 3.7% paraformaldehyde, and stained with 1% crystal violet. Cell viability was assessed using the Cell Titer-Blue kit, and fluorescence intensity (555–585 nm, gain: 57) was measured using a SynergyHTX Fluorescent Microplate Fluorometer. For spheroids, cells were suspended in complete medium, seeded in ultra-low attachment plates, and incubated for four days. The spheroid viability was tested using the Cell Titer-Blue assay after trypsinization. Migration and invasion assays were performed in Transwells with 8-µm-pore filters, uncoated for migration or coated with matrigel for invasion. After incubation, non-migrated or non-invaded cells were removed, and the migrated or invaded cells were fixed, stained with crystal violet, and counted under microscope. Structural modeling, peptides design, and synthesis While this study was ongoing, the cryo-EM structure of human PIWIL2 (Hili, PDB: 7YFX) was published [18]. However, we used the AlphaFold-predicted model in this study, as the two structures showed an overall root mean square deviation of 1.45 Å ( Figure S1 A ). For NME2, we utilized its crystal structure (PDB: 7KPF) to analyze its binding with PIWIL2. For HDAC3, the crystal structure (PDB: 4A69) [19] lacks the C-terminal domain (aa 376–428), which potentially interact with PIWIL2 [20]. To address this, we retrieved the full-length HDAC3 model from the AlphaFold database for docking analysis. Protein-protein docking was performed using ClusPro, MOE, and AlphaFold to generate high-confidence models consistent with experimental interactions. AlphaFold models were generated five times with varying random seeds. Models deviating from experimental data were excluded. For NME2 and HDAC3, ten docking poses per tool were analyzed to identify consensus binding interfaces. Final models underwent molecular dynamics simulations and binding free energy (BFE) calculations using MMPBSA methods [21]. Critical binding motifs within HDAC3 and NME2 contributing to BFE and interface stability were identified and subjected to in silico alanine mutagenesis [22]. These motifs served as templates to design synthetic decoy peptides (NEP1, NEP2, and HDEP1) targeting PIWIL2's interaction with HDAC3 or NME2. Peptide candidates were docked against PIWIL2, linked to a cell-penetrating peptide (CPP), and synthesized for in vitro studies. Additionally, FoldNucleus [23, 24] was used to identify fragments of the folding nucleus in the Middle Domain (MID) and PIWI domains of PIWIL2 to disrupt its folding. Two peptides, FONB1 and FONB2, were selected: FONB1 mimics the MID domain's core beta sheet, while FONB2 mimics a helix in the PIWI domain ( Figure S1 B ). All peptides were linked with CPP by their N-terminal and synthesized by CUSABIO (GeneCust, Boynes, France) at a purity of over 90%, as determined by reversed-phase high-performance liquid chromatography (HPLC; Shimadzu Prominence), described previously [22]. The HPLC reports and related information about peptide synthesis are provided in supplementary data ( see Supplementary data ). Statistics and reproducibility All the statistical analysis was performed using SigmaPlot v12.5 software (Systat Software, Inc., San Jose, CA, USA), R packages (www.r-project.org), and GraphPad Prism (version 7). All experiments were performed in triplicate, and the data are represented as the mean ± standard deviation. *P < 0.05, **P < 0.01, and ***P < 0.001 compared to siNC or vector group. Significant difference was determined using the two-tailed Student’s t-test or One Way ANOVA Tukey test. P < 0.05 was considered statistically significant. Data were analyzed using SigmaPlot software (Systat Software, Inc.) to evaluate the two parameters (logistic three and quadratic) and determine the IC50 of the peptide or drug. The isobologram analysis [25] evaluates the nature of interaction of two drugs, i.e., drug A and drug B, at a given effect level. Combination index (CI) is calculated as below: $$\:CI=\:\frac{{C}_{A,x}}{{IC}_{x,A}}+\:\frac{{C}_{B,x}}{{IC}_{x,B}}$$ A CI of less than, equal to, and more than 1 indicates synergy, additivity, and antagonism, respectively. Results Identification of SLC39A14-PIWIL2 fusion transcript in HCC We used three methods—SOAPfuse, ChimeraScan, and TopHat-Fusion—to identify tumor-specific fusion transcripts with over 30 chimeric reads at the breakpoint involving protein-coding genes. Fourteen potential fusion transcripts were consistently detected by all methods (Fig. 1 A). While no recurrent fusions were observed, we hypothesized that functional fusions might be expressed at higher levels than native transcripts. Among these, the SLC39A14-PIWIL2 fusion exhibited the highest expression (4.5-fold) relative to its native form (Fig. 1 B). This fusion, caused by a chromosomal inversion on chromosome 8, joins exon 1 of SLC39A14 with exons 7–23 of PIWIL2 (Fig. 1 C). Expasy Translate predicted the resulting ~ 82.48 kDa PIWIL2 protein (tPIWIL2), with exon 1 of SLC39A14 not contributing to the functional ORF (Fig. 1 D, Figure S2 A ). AlphaFold modeling revealed that tPIWIL2 lacks the intrinsically disordered (ID) region and the L0 motif in the N-terminal domain required for RNA binding but retains the PAZ, MID, and PIWI domains (Fig. 1 D). Sanger sequencing confirmed SLC39A14-PIWIL2 expression at the RNA level in the HCC sample (AJHCC007) but not at the genomic DNA level (Fig. 1 E). Interestingly, SLC39A14 expression in HCC samples, including AJHCC007, was lower than in non-tumor samples, while PIWIL2 expression was markedly elevated in AJHCC007. However, SLC39A14 levels remained higher than PIWIL2 in other HCC and control samples, suggesting liver-specific induction (Fig. 1 F, Figure S2 B ) [26]. Using the Tumor Fusion Gene Data Portal (TCGA), we identified SLC39A14-PIWIL2 fusions in stomach adenocarcinoma (STAD) and lung squamous cell carcinoma (LUSC), with breakpoints differing from those in AJHCC007 ( Figure S2 C ). In STAD, the fusion encodes full-length PIWIL2, while in LUSC, it produces a shorter PIWIL2 (530 aa, 60.7 kDa) similar to PL2L60, which promotes tumorigenesis via NF-κB [27]. Despite varying lengths, all forms are associated with tumorigenesis when expressed outside the testis. SLC39A14-PIWIL2 (tPIWIL2) promotes HCC progression SLC39A14 maintains metal ion homeostasis in the liver and pancreas, resulting in higher expression in these organs compared to others, as indicated by the Human Protein Atlas dataset ( Figure S3A ) [26]. Conversely, PIWIL2, a member of the PIWI subfamily of Argonaute proteins, is crucial for genome integrity during germ cell development and is predominantly expressed in the testis and duodenum, with minimal expression in liver tissues ( Figure S3B ) [28]. These observations suggest that the rearrangement of SLC39A14 exon 1 into the 5' exon 7 of PIWIL2 likely enhances PIWIL2 expression in HCC. We hypothesized that SLC39A14-PIWIL2 expression in HCC is driven by the SLC39A14 promoter. RT-PCR analysis of the predicted promoter region (1000 bp) in AJHCC007 confirmed transcriptional activity, suggesting that the SLC39A14 promoter and exon 1 are rearranged into the 5′ region of PIWIL2 exon 7, inducing aberrant PIWIL2 expression ( Figure S3C ). Since abnormal transcripts or proteins are often degraded via mechanisms like nonsense-mediated mRNA decay or the ubiquitin-proteasome system [29], we sought to determine whether SLC39A14-PIWIL2 produces a functional protein. We cloned and expressed WT PIWIL2, SLC39A14-PIWIL2, and tPIWIL2 (without exon 1) in Huh7 and HepG2 cells. RT-PCR and Western blot analyses confirmed the expression of tPIWIL2 and SLC39A14-PIWIL2 at similar molecular weights (~ 80 kDa), consistent with exon 1 of SLC39A14 not contributing to the functional ORF (Fig. 2 A, Figure S3D ). These results validate that SLC39A14-PIWIL2 encodes a functional PIWIL2 protein (tPIWIL2). Aberrant PIWIL2 expression has been implicated in promoting proliferation in HCC and other cancers [30, 31], with its tumorigenic functions mediated through interactions with HDAC3, NME2, β-catenin (CTNNB1), and others via the PIWI and MID domains [20, 27, 31, 32]. In agreement, we demonstrated that tPIWIL2, like WT PIWIL2, enhances proliferation, invasion, and migration of liver cancer cells (HepG2 and Huh7, Fig. 2 B). These findings confirm that the SLC39A14-PIWIL2 fusion transcript expresses an oncogenic tPIWIL2 protein, retaining its functional PIWI and MID domains. Structural insights into the PIWIL2 binding proteins, NME2 and HDAC3 To explore the downstream pathways contributing to the tumor-promoting functions of the PIWIL2 fusion product, we focused on two known PIWIL2-binding proteins, NME2 and HDAC3. To gain structural insights into their interactions with PIWIL2, both molecules were docked with PIWIL2 using multiple state-of-the-art protein-protein docking tools (Fig. 2 C). It is reported that NME2, but not its homolog NME1, binds PIWIL2 [31]. To understand this specificity, we aligned the sequences of NME1 and NME2, identifying critical amino acid differences that influence PIWIL2 binding (Fig. 2 C, left ). Structural analysis revealed that NME2 interacts with both the MID and PIWI domains of PIWIL2 via residues unique to NME2 (Fig. 2 D, left ). Meanwhile, HDAC3 binds exclusively to the PIWI domain of PIWIL2, utilizing a C-terminal helix motif consistent with previous findings (Fig. 2 D, right ) [20]. To evaluate the stability of these interactions, MDS were performed on the PIWIL2-NME2 and PIWIL2-HDAC3 complexes. BFE calculations and hydrogen bond density analyses demonstrated that both complexes maintained approximately 7.5 hydrogen bonds on average (Fig. 3 A). Interestingly, BFE analyses revealed that PIWIL2 binds HDAC3 with greater affinity than NME2 (Fig. 3 B), likely due to the higher number of electrostatic bonds observed in the PIWIL2-HDAC3 complex (Fig. 2 D, right ). Root mean square fluctuation analysis indicated that the N and PAZ domains of PIWIL2 exhibit higher flexibility compared to the MID and PIWI domains, with the latter being further stabilized upon binding to NME2 and HDAC3 (Fig. 3 C). These findings underscore the importance of HDAC3 and NME2 in mediating PIWIL2's oncogenic functions, with interactions occurring primarily through the MID and PIWI domains, independent of the N-terminal and PAZ domains. PIWIL2 inhibiting peptides design and in vitro validation Given the critical role of the PIWIL2-HDAC3 and PIWIL2-NME2 binding in initiating oncogenic pathways, we used in silico alanine mutagenesis and identified two critical motifs in NME2 (amino acids 34–56 and 115–140) and a helical motif in HDAC3 (amino acids 351–370) that significantly contribute to the binding energies of their respective complexes (Fig. 4 A). Based on these insights, we designed decoy peptides that could selectively disrupt these interactions, using decoy-based peptide design strategy (Fig. 4 B). We have previously utilized this strategy in designing TLRs inhibiting peptides [33]. Peptides, NEP1, NEP2, and HDEP1, outcompete HDAC3 and NME2 for PIWIL2 binding, as suggested by the peptides clustering around MID and PIWI domains of PIWIL2 (Fig. 4 C). This competitive binding is expected to attenuate the PIWIL2-mediated stabilization of HDAC3, the c-Myc regulatory function of NME2 and downstream oncogenic effects, such as cell proliferation, and modulation of critical signaling pathways like Wnt and Src/STAT3. Additionally, we developed folding nucleus-blocking peptides (FONB1, FONB2) to prevent proper folding of aberrantly expressed PIWIL2 in HCC. This strategy builds on our prior work with TLR-inhibiting peptides [34]. In addition, the same strategy was utilized to block the folding of HIV-1 protease by utilizing a peptide segment that is identical to the folding nucleus [35]. FONB1 mimics the core β-sheet of the MID domain, while FONB2 targets a PIWI domain helix (Fig. 4 D, Figure S1 B). Using liver cancer cell lines (Huh7, HepG2, SNU449, SNU398) overexpressing PIWIL2 ( Figure S4A ), we assessed peptide efficacy through cell viability and sphere formation assays. NEP1 consistently demonstrated the highest potency, achieving IC50 values of 8 µM in SNU398 and 11 µM in SNU449 for cell viability assays, and 9.6 µM (Huh7) and 8.6 µM (SNU398) in sphere formation assays. HDEP1 showed moderate activity, with IC50 values of 10 µM (SNU398) and 28 µM (SNU449) for cell viability, and 10 µM (Huh7) and 9.9 µM (SNU398) for sphere formation. FONB1 and FONB2 exhibited higher IC50 values, indicating lower potency (Fig. 4 E, F). These findings identify NEP1 as the most effective peptide, significantly inhibiting PIWIL2-mediated oncogenic pathways across all assays and cell lines. NEP1 suppresses liver cancer oncogenesis by targeting the PIWIL2 pathway To investigate NEP1's effects on the PIWIL2 pathway, we analyzed RNA levels of PIWIL2-associated proteins in SNU398 and SNU449 cells. PIWIL2 overexpression significantly upregulated CTNNB1, c-myc, K8, and NME2 transcripts (Fig. 5 A), while treatment with 10 µM NEP1 suppressed these changes, indicating NEP1's regulatory impact. Immunoblotting confirmed elevated p-AKT, GSK3β, and c-myc levels in PIWIL2-overexpressing cells, which NEP1 treatment restored to baseline (Fig. 5 B). This aligns with prior findings that PIWIL2 knockdown reduces AKT and GSK3β phosphorylation [36]. Discrepancies in CTNNB1 mRNA and protein levels may result from p-GSK3β-mediated β-catenin stabilization, which increases protein accumulation without altering transcription [37–39]. Thus, RT-qPCR reflects CTNNB1 transcription, while immunoblotting captures post-translational regulation. Next, immunocytochemistry was performed to assess c-myc subcellular localization under PIWIL2 overexpression and NEP1 treatment. PIWIL2 caused significant nuclear accumulation of c-myc in both cell lines, which NEP1 effectively reversed (Fig. 5 C). This aligns with previous findings that PIWIL2 interacts with NME2 to promote c-myc-driven proliferation in HeLa and HepG2 cells [31]. NEP1, in contrast, suppresses c-myc expression, inhibiting cell proliferation. 5-Fluorouracil (5-FU) is a pyrimidine analog that disrupts DNA and RNA synthesis [40] and is used to treat various cancers, including colorectal, breast, gastric, pancreatic, and head and neck malignancies [41]. We examined the combined effects of NEP1 and 5-FU on liver cancer cell lines (Fig. 4 D). PIWIL2 overexpression increased the IC50 of 5-FU but decreased the IC50 of NEP1. Co-administration of NEP1 and 5-FU at equal concentrations (0, 2, 5, 10, 25, and 50 µM) reduced the IC50 of the combination under PIWIL2 overexpression. CI analysis showed antagonism at IC30 but synergy at IC50, with CI values of 0.693 and 0.842 in SNU398 and SNU449, respectively. These findings suggest that NEP1 reverses PIWIL2-driven oncogenic changes, including c-myc nuclear accumulation and chemoresistance, and synergistically enhances 5-FU efficacy, supporting its potential as a targeted cancer therapy. This approach also highlights opportunities for personalized treatment strategies targeting specific molecular drivers. Discussion This study identifies a chromosomal inversion on chromosome 8 in 68 HCC patient samples, fusing exon 1 of SLC39A14 with exons 7–23 of PIWIL2, forming the SLC39A14-PIWIL2 fusion gene. The rearrangement activates the SLC39A14 promoter, which drives the expression of PIWIL2, an oncogene typically restricted to gonads [42], leading to low molecular weight PIWIL2 (tPIWIL2) overexpression. This promotes HCC progression by activating oncogenic pathways. Fusion-driven oncogenesis often involves promoter activation of oncogenes by tissue-specific or highly expressed genes. For example, TMPRSS2-ERG and SLC45A3-BRAF fusions in prostate cancer similarly amplify oncogene expression via highly active promoters [43]. The SLC39A14-PIWIL2 fusion follows this mechanism, with the SLC39A14 promoter driving PIWIL2 overexpression, amplifying its tumor-promoting potential in HCC. PIWIL2 promotes tumorigenesis through interactions with key proteins and pathways. It stabilizes HDAC3 via its PIWI domain by preventing degradation and enhancing phosphorylation by CK2α, promoting cell proliferation and suppressing apoptosis [20]. It interacts with NME2, supporting c-Myc-mediated oncogenesis [31], and binds β-catenin via its PAZ domain, implicating the Wnt signaling pathway [32]. Additionally, PIWIL2 inhibits apoptosis by forming a PIWIL2/K8/p38 complex, stabilizing K8, reducing Fas, and repressing p53 phosphorylation [44]. These multifaceted interactions make PIWIL2 a critical driver of oncogenesis and a promising therapeutic target. The protein product of the SLC39A14-PIWIL2 fusion retains the oncogenic MID and PIWI domains of PIWIL2, driving proliferation, invasion, and migration in Huh7 and HepG2 cells despite losing the intrinsically disordered region and L0 motif. Interestingly, similar fusion transcripts were found in STAD and LUSC, with distinct breakpoints and functions. In LUSC, the truncated PIWIL2 isoform resembles PL2L60, associated with NF-κB activation and tumorigenesis [27], underscoring its potential as a universal therapeutic target. Our structural modeling revealed that tPIWIL2 interacts with HDAC3 and NME2 via its MID and PIWI domains, thereby potentially driving its aberrant oncogenicity in liver tissues. Therefore, key residues essential for these interactions were identified through molecular dynamics simulations and alanine mutagenesis, enabling the design of decoy peptides (NEP1 and HDEP1) to competitively disrupt these interactions. Current HCC treatments, such as immune checkpoint inhibitors and multi-kinase inhibitors, face limitations due to tumor heterogeneity and resistance [45]. Targeting PIWIL2 through small molecules, RNA-based approaches, or peptide therapeutics offers a novel strategy for addressing these challenges. The peptides developed in this study effectively attenuate PIWIL2-mediated oncogenic signaling, demonstrating therapeutic potential. Moreover, the SLC39A14-PIWIL2 fusion could serve as a biomarker for early diagnosis and disease stratification. Detecting fusion transcripts in serum, as shown with other fusions like SLC45A2-AMACR [46], could enable minimally invasive diagnostic assays tailored to HCC. Limitations and Future Directions We identified a rare case of SLC39A14-PIWIL2 expression in HCC, with evidence of its occurrence in other cancer types. Although the expression frequency of the fusion transcript is low, targeted therapies against this fusion may provide promising approach for managing patients harboring this alteration. In addition, this study establishes the oncogenic role of SLC39A14-PIWIL2 in HCC, however, further investigation is needed to elucidate its role in the tumor microenvironment and its interplay with immune evasion mechanisms. Future studies should also focus on optimizing the delivery and stability of PIWIL2-inhibiting peptides for in vivo applications. Although we partly evaluated (5-FU), combining these targeted therapies with existing treatment modalities, such as immune checkpoint inhibitors or kinase inhibitors, could provide synergistic benefits and overcome resistance mechanisms in advanced HCC. Declarations Funding Declaration This research was supported by grants from the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT), Republic of Korea (NRF-2019R1A5A2026045) and a grant from the Korea Health Industry Development Institute (KHIDI) funded by the Ministry of Health & Welfare, Republic of Korea (HR21C1003 and HV22C0164, and RS-2024-00407544). This work was supported by KREONET (Korea Research Environment Open NETwork), managed and operated by KISTI (Korea Institute of Science and Technology Information). Ethics approval and consent to participate The Institutional Review Board of Ajou University Hospital has approved this study and waived the need for informed consent from donors (IRB No. AJIRB-GEN-GEN-12). Availability of data and material The raw data of the genomic profiles are available in the GEO database (http://www.ncbi.nlm.nih.gov/projects/geo) under ac cession number GSE113617. Declaration of competing interests No competing interest to declare. However, all data and subsequent analyses were conducted without the use of AI tools, except for AlphaFold 3 sever, which was used for protein model construction. Authors' contributions M.S. and H.G.W. designed and conceptualized the study and performed data analyses. J.-H.C. and M.J.K. performed data analysis. S.U.M. and M.J.K performed experiments. M.S. J.-H.C. and S.U.M. wrote the manuscript. H.G.W. wrote the manuscript, supervised and funded the study. References A. Suresh, R. Dhanasekaran, Implications of genetic heterogeneity in hepatocellular cancer, Adv Cancer Res 156 (2022) 103–135. w.b.e. Cancer Genome Atlas Research Network. Electronic address, N. Cancer Genome Atlas Research, Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma, Cell 169(7) (2017) 1327–1341 e23. D. Cui, W. Li, D. Jiang, J. Wu, J. Xie, Y. 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LaFargue, J. Siddiqui, F. Demichelis, P. Moeller, T.A. Bismar, R. Kuefer, D.R. Fullen, T.M. Johnson, J.K. Greenson, T.J. Giordano, P. Tan, S.A. Tomlins, S. Varambally, M.A. Rubin, C.A. Maher, A.M. Chinnaiyan, Rearrangements of the RAF kinase pathway in prostate cancer, gastric cancer and melanoma, Nat Med 16(7) (2010) 793-8. S. Jiang, L. Zhao, Y. Lu, M. Wang, Y. Chen, D. Tao, Y. Liu, H. Sun, S. Zhang, Y. Ma, Piwil2 inhibits keratin 8 degradation through promoting p38-induced phosphorylation to resist Fas-mediated apoptosis, Mol Cell Biol 34(21) (2014) 3928-38. D.S. Mandlik, S.K. Mandlik, H.B. Choudhary, Immunotherapy for hepatocellular carcinoma: Current status and future perspectives, World J Gastroenterol 29(6) (2023) 1054–1075. Z.H. Zuo, Y.P. Yu, B.G. Ren, S. Liu, J. Nelson, Z. Wang, J. Tao, T. Pradhan-Sundd, R. Bhargava, G. Michalopoulos, Q. Chen, J. Zhang, D. Ma, A. Pennathur, J. Luketich, P. Satdarshan Monga, M. Nalesnik, J.H. Luo, Oncogenic Activity of Solute Carrier Family 45 Member 2 and Alpha-Methylacyl-Coenzyme A Racemase Gene Fusion Is Mediated by Mitogen-Activated Protein Kinase, Hepatol Commun 6(1) (2022) 209–222. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx SupplementarymaterialPeptidepurityHPLCMS.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 08 Sep, 2025 Reviews received at journal 04 Sep, 2025 Reviews received at journal 22 Aug, 2025 Reviewers agreed at journal 14 Aug, 2025 Reviewers agreed at journal 14 Aug, 2025 Reviewers invited by journal 07 Aug, 2025 Editor assigned by journal 30 Jul, 2025 Submission checks completed at journal 29 Jul, 2025 First submitted to journal 25 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7217926","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":498277983,"identity":"35ab5298-efef-4b28-97b5-bf0f796e2a40","order_by":0,"name":"Masaud Shah","email":"","orcid":"","institution":"Ajou University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Masaud","middleName":"","lastName":"Shah","suffix":""},{"id":498277984,"identity":"b42cf77d-b7aa-474a-9748-84e610eab2f0","order_by":1,"name":"Sung Ung Moon","email":"","orcid":"","institution":"Ajou University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Sung","middleName":"Ung","lastName":"Moon","suffix":""},{"id":498277985,"identity":"9d475075-8883-4ecb-b613-93171a6ca4a1","order_by":2,"name":"Ji-Hye Choi","email":"","orcid":"","institution":"Ajou University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ji-Hye","middleName":"","lastName":"Choi","suffix":""},{"id":498277986,"identity":"f5d7d627-74f1-4cc6-b4ee-5b0de2ddcf1f","order_by":3,"name":"Min Jae Kim","email":"","orcid":"","institution":"Ajou University","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"Jae","lastName":"Kim","suffix":""},{"id":498277987,"identity":"daa528d8-abc6-4c45-b611-396aa66070f4","order_by":4,"name":"Hyun Goo Woo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArUlEQVRIiWNgGAWjYBACAwbmAwwSEDYzsVrYEkjWwmMAYxOpxZx/zccPFhWHGfjbDzAbVxCjxXLG280SEmcOM0icSWBOPEOUw26c3SAh2XaYgeEGA/PBBuK0nHn8A6RFnngt53vYwLYYALUkEmkLm5mFxJl0HsMzic2GRNpy+PFtiQprObnjhw9LEqWFQSKBgRkYlTwMDIzEaWBg4D/AwPiBSLWjYBSMglEwQgEA4g4xLfirtNoAAAAASUVORK5CYII=","orcid":"","institution":"Ajou University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Hyun","middleName":"Goo","lastName":"Woo","suffix":""}],"badges":[],"createdAt":"2025-07-26 02:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7217926/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7217926/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89065934,"identity":"1b03dc6c-e7cd-4819-a786-631245ee7de8","added_by":"auto","created_at":"2025-08-14 10:42:26","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":979977,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of the SLC39A14-PIWIL2 fusion transcript in HCC. \u003c/strong\u003e(A) Workflow of potential fusion transcripts identification using three different methods. (B) Bar plot showing the expression fold difference of the fusion products in HCC samples. PIWIL2 gene expression levels across 68 HCC patients. (C) Fusion structure of the SLC39A14-PIWIL2 transcript. (D) A 3D protein model of the full-length and tPIWIL2 proteins. (E) Aligned reads at the breakpoint of the SLC39A14-PIWIL2 fusion transcript in patient AJHCC007 (top). Sanger sequencing validations using genomic DNA (gDNA) and complementary DNA (cDNA) (bottom). (F) Boxplots showing the expression levels of SLC39A14 (left) and PIWIL2 (right) across three groups: HCCs without the SLC39A14-PIWIL2 fusion, HCCs with the fusion, and non-tumor samples.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7217926/v1/9238eb0771e9be6a34bf8162.jpeg"},{"id":89066457,"identity":"40697005-236f-41f4-bb3f-b17036619605","added_by":"auto","created_at":"2025-08-14 10:42:41","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1132489,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIn vitro and in silico characterization of tPIWIL2 and protein-protein interaction\u003c/strong\u003e. (A)\u003cstrong\u003e \u003c/strong\u003eProtein expression of the fused and non-fused forms of PIWIL2 proteins. (B) Phenotypic effects of PIWIL2 protein products on the Huh7 and HepG2 cell lines. (C) Interaction of PIWIL2 with NME2 and HDAC3. Residues in NME2 that differ from NME1 are highlighted in red within the aligned sequences. The PIWIL2-binding motif in HDAC3, located in the C-terminal region of the full-length protein, is also highlighted in red. An overview of the computational strategy used to predict interactions of PIWIL2 with its binding partners, HDAC3 and NME2, is shown. (D) The binding interface of MID-PIWI domains of PIWIL2 with NME2 (left) and PIWIL2 with HDAC3 (right) are shown.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7217926/v1/9f339fd09855b6feae310a33.jpeg"},{"id":89066004,"identity":"3d3c910a-8664-48aa-a455-52c1e2bdb2fd","added_by":"auto","created_at":"2025-08-14 10:42:29","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":653795,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStructural modeling and stability evaluation of the PIWIL2 proteins.\u003c/strong\u003e (\u003cstrong\u003eA\u003c/strong\u003e) Line and density plots showing changes in the number of hydrogen bonds of PIWIL2 with NME2 and HDAC3. (\u003cstrong\u003eB\u003c/strong\u003e) Binding free energy of PIWIL2 with NME2 and HDAC3 calculated through MMPBSA methods are depicted in a bar plots. (\u003cstrong\u003eC\u003c/strong\u003e) RMSF and RMSD plots of the PIWIL2 protein in complex with NME2 (nme) and HDAC3 (hd) or in its apo form (without binding partners) are shown.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7217926/v1/05c95f604d864e1f57f02335.jpeg"},{"id":89066442,"identity":"0e2db796-9237-46d4-978c-6b940d79d98f","added_by":"auto","created_at":"2025-08-14 10:42:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1250449,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnti-PIWIL2 peptides design and in vitro evaluation. \u003c/strong\u003e(A) Hotspot residues identification in NME2 using in silico alanine scanning at the PIWIL2-NME2 interface (top) and PIWIL2-HDAC3 interface (bottom) are shown. (B) NME2-based PIWIL2-inhibiting peptides, NEP1 and NEP2 (top) and HDAC3-based PIWIL2-inhibiting peptide, HDEP1 are shown. (C) NEP1 and NEP2 peptides docked onto PIWIL2 (top) and HDEP1 peptide docked onto PIWIL2 (bottom) are shown. (D) Folding nucleus-based peptides design against PIWI and MID domains of PIWIL2. (E) Cell viability, is presented for PIWIL2-overexpressing liver cancer cell lines following treatment with four peptides (NEP1, HDEP1, FONB1, and FONB2). (F)\u003cstrong\u003e \u003c/strong\u003eCell viability during sphere formation assays is shown for PWILL2-overexpressing liver cancer cell lines after treatment peptides.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7217926/v1/39a969af55d8c5a5d35ff3d2.png"},{"id":89065895,"identity":"294df8ac-672d-4a54-88d3-b16d4e646cf7","added_by":"auto","created_at":"2025-08-14 10:42:24","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1013087,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTherapeutic effect of PWILL2-inhibiting peptides. \u003c/strong\u003e(A)\u003cstrong\u003e \u003c/strong\u003eRT-qPCR analysis showing the expression of PIWIL2, CTNNB1, c-myc, TP53, Cyclin D, K8, and hNME2 following treatment with NEP1 peptide. The effect of peptide was compared to that of vector-expressing and PIWIL-2-expressing peptide-untreated cells. Relative mRNA levels of target genes were normalized to GAPDH. (B) Immunoblotting of CTNNB1, p-STAT3, c-Akt, c-myc, and p-GSK3 under the same conditions. (C)\u003cstrong\u003e \u003c/strong\u003eImmunocytochemical analysis of c-myc localization was performed in PIWIL2-overexpressing cells. Fluorescence intensities were quantified and expressed as percentages relative to vector. Statistical significance is denoted as *P \u0026lt; 0.05, **P \u0026lt; 0.01, and ***P \u0026lt; 0.001 vs. vector. (D) To synergistic effect of 5-FU and NEP1. Cell viability assays were conducted to determine the Combination Index (CI). The control groups included cells treated with the vector alone followed by treatment with 5-FU, scramble peptide, or NEP1, as well as cells treated with both the PIWIL2-overexpressing plasmid and the scramble peptide. For CI analysis, IC30, IC50, and IC70 values were determined by treating cells with varying concentrations of 5-FU and NEP1 individually. These values were then compared to those obtained from simultaneous treatment with 5-FU and NEP1 at the varying concentrations, allowing for CI calculation. CI \u0026gt; 1 was defined as antagonism, CI = 1 as an additive effect, and CI \u0026lt; 1 as synergism.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7217926/v1/dd8b73724f13631b775baf77.png"},{"id":89069158,"identity":"d5b697da-f1c5-429f-9629-8eec150a0ec7","added_by":"auto","created_at":"2025-08-14 10:50:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5647643,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7217926/v1/e16f6bd7-5273-4218-b6dd-0575135c183e.pdf"},{"id":89065857,"identity":"79f860af-0ee8-4d65-aaf2-f23051c31b8e","added_by":"auto","created_at":"2025-08-14 10:42:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":10629097,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7217926/v1/de312d73afd9166ec1f766a9.docx"},{"id":89065977,"identity":"70218eab-89dd-4726-8e0e-119fd030a889","added_by":"auto","created_at":"2025-08-14 10:42:28","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":791990,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarymaterialPeptidepurityHPLCMS.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7217926/v1/ccabb09459910904f75f2d30.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Peptide‑Based Therapeutics Targeting the SLC39A14‑PIWIL2 Fusion in Hepatocellular Carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMolecular and genetic complexity of Hepatocellular Carcinoma (HCC) impedes early diagnosis and limits treatment efficacy, thereby contributing to poor survival outcomes [1]. Advances in high-throughput genomic sequencing have unraveled the intricate molecular prerequisites of HCC, revealing its molecular heterogeneity with aberrations across various pathways, including inflammation, cell cycle control, invasion, metabolism, and metastasis [2\u0026ndash;4]. In addition, chromosomal rearrangements and fusion genes stand out as critical oncogenic drivers across multiple cancer types [5\u0026ndash;8]. These fusion genes serve as diagnostic biomarkers, such as ERG and ETV1, others like ALK, RET, BRAF, and FGFR1-4 offer actionable therapeutic targets [9, 10]. In HCC, a limited number of fusion genes have been now identified with potential implications in tumor progression and prognosis. The DNAJB1-PRKACA fusion serves as a driver mutation in fibrolamellar carcinoma, a subtype of HCC [11]. The LINE1-MET fusion has also been highlighted in HCC development [12]. Furthermore, fusions such as SLC45A2-AMACR, ITCH-ASIP, and RNF138-RNF125 have been associated with better HCC prognoses, while MAN2A1-FER, CCNH-C5orf30, and SLC45A2-AMACR, detectable in serum, show potential for HCC diagnosis [13].\u003c/p\u003e\u003cp\u003eIn this study, we identified a novel SLC39A14-PIWIL2 fusion gene in HCC patients\u0026rsquo; samples. This fusion was formed by chromosomal inversion, joining SLC39A14 exon 1 with PIWIL2 exons 7\u0026ndash;23 and resulting in the upregulation of PIWIL2 and promoting HCC progression. Additionally, structural modeling of PIWIL2 interactions with downstream proteins, alongside the design of PIWIL2 inhibitory peptides, has further highlighted its potential as a therapeutic target in HCC, opening avenues for the development of PIWIL2-focused treatments.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cb\u003eIdentification of fusion transcripts from RNA-Seq data of HCC patient samples\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe identified the expression of fusion transcripts from our previously published RNA-seq data (68 HCC and 10 non-tumor tissues; GSE113617) [14]. By applying three different methods of SOAPfuse [15], ChimeraScan [16], and TopHat-Fusion [17] with default parameters and filtering out transcripts with fewer than 30 reads at the breakpoints, we could identify 14 fusion transcripts which were detected at least two of the methods.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHuman cancer cell lines, anticancer drug, and plasmids\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe SNU398 (purchased from the Korean Cell Line Bank, Seoul, Republic of Korea (KCLB) Cat# 00398_SNU-398, RRID: CVCL_0077), SNU449 (KCLB Cat# 00449_SNU-449, RRID: CVCL_0454), HepG2 (KCLB Cat# 88065_HepG2, RRID: CVCL_0027), and Huh7 (KCLB Cat# 60104_Huh7, RRID: CVCL_0336) cell lines were cultured in DMEM, MEM, or RPMI1640 (Gibco BRL, Grand Island, NY) supplemented with 10% FBS and 1% antibiotics at 37\u0026deg;C in a 5% CO2 incubator. PIWIL2, tPIWIL2, and SLC39A14-PIWIL2 constructs were cloned into PCDNA3.1 (RRID: Addgene_70219) or C-terminal 3xFLAG-tagged PCDNA3.1 (RRID: Addgene_208616) using the In-Fusion cloning method (Clontech, Mountain View, CA). PCR products were amplified with CloneAmp HiFi PCR Premix (TAKARA, Tokyo, Japan) and specific primers (\u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e), followed by insertion into PCDNA3.1 using HindIII and ApaI. Constructs were confirmed by Sanger sequencing (Macrogen, Seoul, South Korea). The plasmids were transfected into the liver cancer cell lines (2 \u0026times; 10⁶ cells per 60-mm dish) using 6 \u0026micro;g of Lipofectamine 3000 (Invitrogen, Thermo Fisher Scientific, Inc.), and incubated for 48 hours at 37\u0026deg;C in a CO₂ incubator. The cells were treated with various concentrations of 5-FU and peptides (0, 1, 2, 2.5, 5, 10, 12.5, 25, and 50 \u0026micro;M) for 4 days in media supplemented with 10% FBS.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImmunoblotting (western blotting)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCells were harvested and lysed using lysis buffer (REF87787, Thermo Fisher Scientific), then centrifuged at ~\u0026thinsp;13,000 \u0026times;g for 10 min at 4\u0026deg;C. Protein concentrations were determined with a Bradford protein assay kit (#5000006, Bio-Rad, Hercules, CA, USA). Equal amounts (30 \u0026micro;g) of protein were separated using 10% SDS-PAGE (Bio-Rad) and transferred to nitrocellulose membranes (#1620115, Bio-Rad) for immunoblotting. Membranes were washed three times with PBS (Welgene, Gyeongsangbuk-do, Republic of Korea) containing 0.1% Tween 20 (PBST; Sigma-Aldrich), blocked with PBST containing 1% bovine serum albumin (BSA, Bovogen, Melbourne, Australia) for 1 h at room temperature, and incubated with primary antibodies in PBST with 1% BSA overnight at 4\u0026deg;C. After washing, membranes were incubated with secondary antibodies (1:1000 dilution) against goat anti-rabbit IgG-HRP (Cell Signaling Technology Cat# 7074S, RRID: AB_2099233) or anti-mouse IgG-HRP (Cell Signaling Technology Cat# 7076S, RRID: AB_330924) for 1 h at room temperature and washed again. Membranes were developed with ECL Buffer (REF34580, Thermo Fisher Scientific) and images captured using an iBright 1500 imaging system (REF34580, Thermo Fisher Scientific). The following antibodies were used: FLAG (1:1000, Sigma-Aldrich, Cat# F1804, RRID: AB_262044), CTNNB1 (1:1000, Santa Cruz Biotechnology, Cat# sc-7963, RRID: AB_626807), c-myc (1:1000, Cell Signaling Technology, Cat# 9402, RRID: AB_2151827), p-Akt (1:1000, Cell Signaling Technology Cat# 4060S, RRID:AB_2315049), p-GSK-3β (1:1000, Cell Signaling Technology, Cat# 9336S, RRID: AB_331405), p-STAT3 (1:1000, Cell Signaling Technology, Cat# 9145S, RRID: AB_2491009), β-actin (1:2000, Santa Cruz Biotechnology, Cat# sc-47778, RRID:AB_626632), and GAPDH (1:5000, Abcam Cat# ab8245, RRID: AB_2107448).\u003c/p\u003e\u003cp\u003e\u003cb\u003eImmunocytochemistry analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo examine c-myc localization, PIWIL2-overexpressing liver cancer cells were incubated with or without NEP1 peptide, fixed with 4% paraformaldehyde, and permeabilized with 0.25% Triton X-100. After washing, cells were blocked with 1% BSA and 0.1% Tween 20 for 1 h, then treated with primary antibodies against c-myc (1:100, Cell Signaling Technology, Cat# 9402, RRID: AB_2151827) and PIWIL2 (1:100, Abnova, Cat# MAB0843, RRID: AB_1204794) at 4\u0026deg;C for 24 h. Following primary antibody incubation, cells were incubated with Alexa Fluor 594-conjugated donkey anti-rabbit IgG (1:200, Molecular Probes Cat# A-21207, RRID: AB_141637) and Alexa Fluor 488-conjugated donkey anti-mouse IgG (1:200, Molecular Probes Cat# A-21202, RRID: AB_141607) secondary antibodies for 2 h at room temperature. Nuclei were stained with DAPI-containing mounting solution, and cells were visualized under an Axiovert 200 fluorescence microscope (Carl Zeiss).\u003c/p\u003e\u003cp\u003e\u003cb\u003eRT-quantitative PCR analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTotal RNA was isolated using RNeay (Qiagen, Hilden, Germany) for RT-qPCR analysis of target genes. RT-qPCR was performed using the iQ SYBR Green supermix (Bio-Rad, CA, USA) and the CFX96\u0026trade; Real-Time system (Bio-Rad, Singapore). Reverse transcription was performed using TOPscript\u0026trade; RT DryMIX (Enzynomics, Daejeon, Republic of Korea). The relative amounts of target genes were normalized to those of glyceraldehyde-3-phosphate dehydrogenase (GAPDH). The primer sets used are listed in table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e in supplementary data. The 2\u003csup\u003e\u0026minus;ΔΔCq\u003c/sup\u003e method was adopted to determine the fold changes (control vs. sample).\u003c/p\u003e\u003cp\u003e\u003cb\u003eCell viability, spheroid formation, migration and invasion assay\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor phenotypic changes due to PIWIL2 overexpression, cells were seeded in 96-well plates (2\u0026times;10\u0026sup3; cells/well) and incubated overnight at 37\u0026deg;C with 5% CO₂. After transfection, 5 mg/mL MTT solution was added and incubated for 2 h. The blue precipitate was dissolved in 150 \u0026micro;l DMSO, and absorbance at 550 nm was measured using a microplate reader. All experiments were done in triplicate. For colony formation, cells were transfected for 48 h, then seeded at 500 cells/well in 6-well plates and incubated for 14 days. Colonies were washed, fixed with 3.7% paraformaldehyde, and stained with 1% crystal violet. Cell viability was assessed using the Cell Titer-Blue kit, and fluorescence intensity (555\u0026ndash;585 nm, gain: 57) was measured using a SynergyHTX Fluorescent Microplate Fluorometer. For spheroids, cells were suspended in complete medium, seeded in ultra-low attachment plates, and incubated for four days. The spheroid viability was tested using the Cell Titer-Blue assay after trypsinization. Migration and invasion assays were performed in Transwells with 8-\u0026micro;m-pore filters, uncoated for migration or coated with matrigel for invasion. After incubation, non-migrated or non-invaded cells were removed, and the migrated or invaded cells were fixed, stained with crystal violet, and counted under microscope.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStructural modeling, peptides design, and synthesis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWhile this study was ongoing, the cryo-EM structure of human PIWIL2 (Hili, PDB: 7YFX) was published [18]. However, we used the AlphaFold-predicted model in this study, as the two structures showed an overall root mean square deviation of 1.45 \u0026Aring; (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA\u003c/b\u003e). For NME2, we utilized its crystal structure (PDB: 7KPF) to analyze its binding with PIWIL2. For HDAC3, the crystal structure (PDB: 4A69) [19] lacks the C-terminal domain (aa 376\u0026ndash;428), which potentially interact with PIWIL2 [20]. To address this, we retrieved the full-length HDAC3 model from the AlphaFold database for docking analysis.\u003c/p\u003e\u003cp\u003eProtein-protein docking was performed using ClusPro, MOE, and AlphaFold to generate high-confidence models consistent with experimental interactions. AlphaFold models were generated five times with varying random seeds. Models deviating from experimental data were excluded. For NME2 and HDAC3, ten docking poses per tool were analyzed to identify consensus binding interfaces.\u003c/p\u003e\u003cp\u003eFinal models underwent molecular dynamics simulations and binding free energy (BFE) calculations using MMPBSA methods [21]. Critical binding motifs within HDAC3 and NME2 contributing to BFE and interface stability were identified and subjected to in silico alanine mutagenesis [22]. These motifs served as templates to design synthetic decoy peptides (NEP1, NEP2, and HDEP1) targeting PIWIL2's interaction with HDAC3 or NME2. Peptide candidates were docked against PIWIL2, linked to a cell-penetrating peptide (CPP), and synthesized for in vitro studies. Additionally, FoldNucleus [23, 24] was used to identify fragments of the folding nucleus in the Middle Domain (MID) and PIWI domains of PIWIL2 to disrupt its folding. Two peptides, FONB1 and FONB2, were selected: FONB1 mimics the MID domain's core beta sheet, while FONB2 mimics a helix in the PIWI domain (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eAll peptides were linked with CPP by their N-terminal and synthesized by CUSABIO (GeneCust, Boynes, France) at a purity of over 90%, as determined by reversed-phase high-performance liquid chromatography (HPLC; Shimadzu Prominence), described previously [22]. The HPLC reports and related information about peptide synthesis are provided in supplementary data (\u003cb\u003esee Supplementary data\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistics and reproducibility\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll the statistical analysis was performed using SigmaPlot v12.5 software (Systat Software, Inc., San Jose, CA, USA), R packages (www.r-project.org), and GraphPad Prism (version 7). All experiments were performed in triplicate, and the data are represented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. *P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, and ***P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 compared to siNC or vector group. Significant difference was determined using the two-tailed Student\u0026rsquo;s t-test or One Way ANOVA Tukey test. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Data were analyzed using SigmaPlot software (Systat Software, Inc.) to evaluate the two parameters (logistic three and quadratic) and determine the IC50 of the peptide or drug. The isobologram analysis [25] evaluates the nature of interaction of two drugs, i.e., drug A and drug B, at a given effect level.\u003c/p\u003e\u003cp\u003eCombination index (CI) is calculated as below:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:CI=\\:\\frac{{C}_{A,x}}{{IC}_{x,A}}+\\:\\frac{{C}_{B,x}}{{IC}_{x,B}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eA CI of less than, equal to, and more than 1 indicates synergy, additivity, and antagonism, respectively.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eIdentification of SLC39A14-PIWIL2 fusion transcript in HCC\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe used three methods\u0026mdash;SOAPfuse, ChimeraScan, and TopHat-Fusion\u0026mdash;to identify tumor-specific fusion transcripts with over 30 chimeric reads at the breakpoint involving protein-coding genes. Fourteen potential fusion transcripts were consistently detected by all methods (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). While no recurrent fusions were observed, we hypothesized that functional fusions might be expressed at higher levels than native transcripts. Among these, the SLC39A14-PIWIL2 fusion exhibited the highest expression (4.5-fold) relative to its native form (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). This fusion, caused by a chromosomal inversion on chromosome 8, joins exon 1 of SLC39A14 with exons 7\u0026ndash;23 of PIWIL2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Expasy Translate predicted the resulting\u0026thinsp;~\u0026thinsp;82.48 kDa PIWIL2 protein (tPIWIL2), with exon 1 of SLC39A14 not contributing to the functional ORF (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD, \u003cb\u003eFigure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eA\u003c/b\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAlphaFold modeling revealed that tPIWIL2 lacks the intrinsically disordered (ID) region and the L0 motif in the N-terminal domain required for RNA binding but retains the PAZ, MID, and PIWI domains (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Sanger sequencing confirmed SLC39A14-PIWIL2 expression at the RNA level in the HCC sample (AJHCC007) but not at the genomic DNA level (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). Interestingly, SLC39A14 expression in HCC samples, including AJHCC007, was lower than in non-tumor samples, while PIWIL2 expression was markedly elevated in AJHCC007. However, SLC39A14 levels remained higher than PIWIL2 in other HCC and control samples, suggesting liver-specific induction (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF, \u003cb\u003eFigure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eB\u003c/b\u003e) [26].\u003c/p\u003e\u003cp\u003eUsing the Tumor Fusion Gene Data Portal (TCGA), we identified SLC39A14-PIWIL2 fusions in stomach adenocarcinoma (STAD) and lung squamous cell carcinoma (LUSC), with breakpoints differing from those in AJHCC007 (\u003cb\u003eFigure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eC\u003c/b\u003e). In STAD, the fusion encodes full-length PIWIL2, while in LUSC, it produces a shorter PIWIL2 (530 aa, 60.7 kDa) similar to PL2L60, which promotes tumorigenesis via NF-κB [27]. Despite varying lengths, all forms are associated with tumorigenesis when expressed outside the testis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSLC39A14-PIWIL2 (tPIWIL2) promotes HCC progression\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSLC39A14 maintains metal ion homeostasis in the liver and pancreas, resulting in higher expression in these organs compared to others, as indicated by the Human Protein Atlas dataset (\u003cb\u003eFigure S3A\u003c/b\u003e) [26]. Conversely, PIWIL2, a member of the PIWI subfamily of Argonaute proteins, is crucial for genome integrity during germ cell development and is predominantly expressed in the testis and duodenum, with minimal expression in liver tissues (\u003cb\u003eFigure S3B\u003c/b\u003e) [28]. These observations suggest that the rearrangement of SLC39A14 exon 1 into the 5' exon 7 of PIWIL2 likely enhances PIWIL2 expression in HCC. We hypothesized that SLC39A14-PIWIL2 expression in HCC is driven by the SLC39A14 promoter. RT-PCR analysis of the predicted promoter region (1000 bp) in AJHCC007 confirmed transcriptional activity, suggesting that the SLC39A14 promoter and exon 1 are rearranged into the 5\u0026prime; region of PIWIL2 exon 7, inducing aberrant PIWIL2 expression (\u003cb\u003eFigure S3C\u003c/b\u003e).\u003c/p\u003e\u003cp\u003eSince abnormal transcripts or proteins are often degraded via mechanisms like nonsense-mediated mRNA decay or the ubiquitin-proteasome system [29], we sought to determine whether SLC39A14-PIWIL2 produces a functional protein. We cloned and expressed WT PIWIL2, SLC39A14-PIWIL2, and tPIWIL2 (without exon 1) in Huh7 and HepG2 cells. RT-PCR and Western blot analyses confirmed the expression of tPIWIL2 and SLC39A14-PIWIL2 at similar molecular weights (~\u0026thinsp;80 kDa), consistent with exon 1 of SLC39A14 not contributing to the functional ORF (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, \u003cb\u003eFigure S3D\u003c/b\u003e). These results validate that SLC39A14-PIWIL2 encodes a functional PIWIL2 protein (tPIWIL2).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAberrant PIWIL2 expression has been implicated in promoting proliferation in HCC and other cancers [30, 31], with its tumorigenic functions mediated through interactions with HDAC3, NME2, β-catenin (CTNNB1), and others via the PIWI and MID domains [20, 27, 31, 32]. In agreement, we demonstrated that tPIWIL2, like WT PIWIL2, enhances proliferation, invasion, and migration of liver cancer cells (HepG2 and Huh7, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). These findings confirm that the SLC39A14-PIWIL2 fusion transcript expresses an oncogenic tPIWIL2 protein, retaining its functional PIWI and MID domains.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStructural insights into the PIWIL2 binding proteins, NME2 and HDAC3\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo explore the downstream pathways contributing to the tumor-promoting functions of the PIWIL2 fusion product, we focused on two known PIWIL2-binding proteins, NME2 and HDAC3. To gain structural insights into their interactions with PIWIL2, both molecules were docked with PIWIL2 using multiple state-of-the-art protein-protein docking tools (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). It is reported that NME2, but not its homolog NME1, binds PIWIL2 [31]. To understand this specificity, we aligned the sequences of NME1 and NME2, identifying critical amino acid differences that influence PIWIL2 binding (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, \u003cem\u003eleft\u003c/em\u003e). Structural analysis revealed that NME2 interacts with both the MID and PIWI domains of PIWIL2 via residues unique to NME2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD, \u003cem\u003eleft\u003c/em\u003e). Meanwhile, HDAC3 binds exclusively to the PIWI domain of PIWIL2, utilizing a C-terminal helix motif consistent with previous findings (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD, \u003cem\u003eright\u003c/em\u003e) [20].\u003c/p\u003e\u003cp\u003eTo evaluate the stability of these interactions, MDS were performed on the PIWIL2-NME2 and PIWIL2-HDAC3 complexes. BFE calculations and hydrogen bond density analyses demonstrated that both complexes maintained approximately 7.5 hydrogen bonds on average (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Interestingly, BFE analyses revealed that PIWIL2 binds HDAC3 with greater affinity than NME2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), likely due to the higher number of electrostatic bonds observed in the PIWIL2-HDAC3 complex (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD, \u003cem\u003eright\u003c/em\u003e). Root mean square fluctuation analysis indicated that the N and PAZ domains of PIWIL2 exhibit higher flexibility compared to the MID and PIWI domains, with the latter being further stabilized upon binding to NME2 and HDAC3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). These findings underscore the importance of HDAC3 and NME2 in mediating PIWIL2's oncogenic functions, with interactions occurring primarily through the MID and PIWI domains, independent of the N-terminal and PAZ domains.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003ePIWIL2 inhibiting peptides design and in vitro validation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGiven the critical role of the PIWIL2-HDAC3 and PIWIL2-NME2 binding in initiating oncogenic pathways, we used in silico alanine mutagenesis and identified two critical motifs in NME2 (amino acids 34\u0026ndash;56 and 115\u0026ndash;140) and a helical motif in HDAC3 (amino acids 351\u0026ndash;370) that significantly contribute to the binding energies of their respective complexes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Based on these insights, we designed decoy peptides that could selectively disrupt these interactions, using decoy-based peptide design strategy (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). We have previously utilized this strategy in designing TLRs inhibiting peptides [33]. Peptides, NEP1, NEP2, and HDEP1, outcompete HDAC3 and NME2 for PIWIL2 binding, as suggested by the peptides clustering around MID and PIWI domains of PIWIL2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). This competitive binding is expected to attenuate the PIWIL2-mediated stabilization of HDAC3, the c-Myc regulatory function of NME2 and downstream oncogenic effects, such as cell proliferation, and modulation of critical signaling pathways like Wnt and Src/STAT3.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAdditionally, we developed folding nucleus-blocking peptides (FONB1, FONB2) to prevent proper folding of aberrantly expressed PIWIL2 in HCC. This strategy builds on our prior work with TLR-inhibiting peptides [34]. In addition, the same strategy was utilized to block the folding of HIV-1 protease by utilizing a peptide segment that is identical to the folding nucleus [35]. FONB1 mimics the core β-sheet of the MID domain, while FONB2 targets a PIWI domain helix (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD, \u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB).\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUsing liver cancer cell lines (Huh7, HepG2, SNU449, SNU398) overexpressing PIWIL2 (\u003cb\u003eFigure S4A\u003c/b\u003e), we assessed peptide efficacy through cell viability and sphere formation assays. NEP1 consistently demonstrated the highest potency, achieving IC50 values of 8 \u0026micro;M in SNU398 and 11 \u0026micro;M in SNU449 for cell viability assays, and 9.6 \u0026micro;M (Huh7) and 8.6 \u0026micro;M (SNU398) in sphere formation assays. HDEP1 showed moderate activity, with IC50 values of 10 \u0026micro;M (SNU398) and 28 \u0026micro;M (SNU449) for cell viability, and 10 \u0026micro;M (Huh7) and 9.9 \u0026micro;M (SNU398) for sphere formation. FONB1 and FONB2 exhibited higher IC50 values, indicating lower potency (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE, F). These findings identify NEP1 as the most effective peptide, significantly inhibiting PIWIL2-mediated oncogenic pathways across all assays and cell lines.\u003c/p\u003e\u003cp\u003e\u003cb\u003eNEP1 suppresses liver cancer oncogenesis by targeting the PIWIL2 pathway\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo investigate NEP1's effects on the PIWIL2 pathway, we analyzed RNA levels of PIWIL2-associated proteins in SNU398 and SNU449 cells. PIWIL2 overexpression significantly upregulated CTNNB1, c-myc, K8, and NME2 transcripts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), while treatment with 10 \u0026micro;M NEP1 suppressed these changes, indicating NEP1's regulatory impact. Immunoblotting confirmed elevated p-AKT, GSK3β, and c-myc levels in PIWIL2-overexpressing cells, which NEP1 treatment restored to baseline (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). This aligns with prior findings that PIWIL2 knockdown reduces AKT and GSK3β phosphorylation [36]. Discrepancies in CTNNB1 mRNA and protein levels may result from p-GSK3β-mediated β-catenin stabilization, which increases protein accumulation without altering transcription [37\u0026ndash;39]. Thus, RT-qPCR reflects CTNNB1 transcription, while immunoblotting captures post-translational regulation. Next, immunocytochemistry was performed to assess c-myc subcellular localization under PIWIL2 overexpression and NEP1 treatment. PIWIL2 caused significant nuclear accumulation of c-myc in both cell lines, which NEP1 effectively reversed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). This aligns with previous findings that PIWIL2 interacts with NME2 to promote c-myc-driven proliferation in HeLa and HepG2 cells [31]. NEP1, in contrast, suppresses c-myc expression, inhibiting cell proliferation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e5-Fluorouracil (5-FU) is a pyrimidine analog that disrupts DNA and RNA synthesis [40] and is used to treat various cancers, including colorectal, breast, gastric, pancreatic, and head and neck malignancies [41]. We examined the combined effects of NEP1 and 5-FU on liver cancer cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). PIWIL2 overexpression increased the IC50 of 5-FU but decreased the IC50 of NEP1. Co-administration of NEP1 and 5-FU at equal concentrations (0, 2, 5, 10, 25, and 50 \u0026micro;M) reduced the IC50 of the combination under PIWIL2 overexpression. CI analysis showed antagonism at IC30 but synergy at IC50, with CI values of 0.693 and 0.842 in SNU398 and SNU449, respectively. These findings suggest that NEP1 reverses PIWIL2-driven oncogenic changes, including c-myc nuclear accumulation and chemoresistance, and synergistically enhances 5-FU efficacy, supporting its potential as a targeted cancer therapy. This approach also highlights opportunities for personalized treatment strategies targeting specific molecular drivers.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study identifies a chromosomal inversion on chromosome 8 in 68 HCC patient samples, fusing exon 1 of SLC39A14 with exons 7\u0026ndash;23 of PIWIL2, forming the SLC39A14-PIWIL2 fusion gene. The rearrangement activates the SLC39A14 promoter, which drives the expression of PIWIL2, an oncogene typically restricted to gonads [42], leading to low molecular weight PIWIL2 (tPIWIL2) overexpression. This promotes HCC progression by activating oncogenic pathways.\u003c/p\u003e\u003cp\u003eFusion-driven oncogenesis often involves promoter activation of oncogenes by tissue-specific or highly expressed genes. For example, TMPRSS2-ERG and SLC45A3-BRAF fusions in prostate cancer similarly amplify oncogene expression via highly active promoters [43]. The SLC39A14-PIWIL2 fusion follows this mechanism, with the SLC39A14 promoter driving PIWIL2 overexpression, amplifying its tumor-promoting potential in HCC.\u003c/p\u003e\u003cp\u003ePIWIL2 promotes tumorigenesis through interactions with key proteins and pathways. It stabilizes HDAC3 via its PIWI domain by preventing degradation and enhancing phosphorylation by CK2α, promoting cell proliferation and suppressing apoptosis [20]. It interacts with NME2, supporting c-Myc-mediated oncogenesis [31], and binds β-catenin via its PAZ domain, implicating the Wnt signaling pathway [32]. Additionally, PIWIL2 inhibits apoptosis by forming a PIWIL2/K8/p38 complex, stabilizing K8, reducing Fas, and repressing p53 phosphorylation [44]. These multifaceted interactions make PIWIL2 a critical driver of oncogenesis and a promising therapeutic target.\u003c/p\u003e\u003cp\u003eThe protein product of the SLC39A14-PIWIL2 fusion retains the oncogenic MID and PIWI domains of PIWIL2, driving proliferation, invasion, and migration in Huh7 and HepG2 cells despite losing the intrinsically disordered region and L0 motif. Interestingly, similar fusion transcripts were found in STAD and LUSC, with distinct breakpoints and functions. In LUSC, the truncated PIWIL2 isoform resembles PL2L60, associated with NF-κB activation and tumorigenesis [27], underscoring its potential as a universal therapeutic target. Our structural modeling revealed that tPIWIL2 interacts with HDAC3 and NME2 via its MID and PIWI domains, thereby potentially driving its aberrant oncogenicity in liver tissues. Therefore, key residues essential for these interactions were identified through molecular dynamics simulations and alanine mutagenesis, enabling the design of decoy peptides (NEP1 and HDEP1) to competitively disrupt these interactions.\u003c/p\u003e\u003cp\u003eCurrent HCC treatments, such as immune checkpoint inhibitors and multi-kinase inhibitors, face limitations due to tumor heterogeneity and resistance [45]. Targeting PIWIL2 through small molecules, RNA-based approaches, or peptide therapeutics offers a novel strategy for addressing these challenges. The peptides developed in this study effectively attenuate PIWIL2-mediated oncogenic signaling, demonstrating therapeutic potential. Moreover, the SLC39A14-PIWIL2 fusion could serve as a biomarker for early diagnosis and disease stratification. Detecting fusion transcripts in serum, as shown with other fusions like SLC45A2-AMACR [46], could enable minimally invasive diagnostic assays tailored to HCC.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations and Future Directions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe identified a rare case of SLC39A14-PIWIL2 expression in HCC, with evidence of its occurrence in other cancer types. Although the expression frequency of the fusion transcript is low, targeted therapies against this fusion may provide promising approach for managing patients harboring this alteration. In addition, this study establishes the oncogenic role of SLC39A14-PIWIL2 in HCC, however, further investigation is needed to elucidate its role in the tumor microenvironment and its interplay with immune evasion mechanisms. Future studies should also focus on optimizing the delivery and stability of PIWIL2-inhibiting peptides for \u003cem\u003ein vivo\u003c/em\u003e applications. Although we partly evaluated (5-FU), combining these targeted therapies with existing treatment modalities, such as immune checkpoint inhibitors or kinase inhibitors, could provide synergistic benefits and overcome resistance mechanisms in advanced HCC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by grants from the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT), Republic of Korea (NRF-2019R1A5A2026045) and a grant from the Korea Health Industry Development Institute (KHIDI) funded by the Ministry of Health \u0026amp; Welfare, Republic of Korea (HR21C1003 and HV22C0164, and RS-2024-00407544). This work was supported by KREONET (Korea Research Environment Open NETwork), managed and operated by KISTI (Korea Institute of Science and Technology Information).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Institutional Review Board of Ajou University Hospital has approved this study and waived the need for informed consent from donors (IRB No. AJIRB-GEN-GEN-12).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data of the genomic profiles are available in the GEO database (http://www.ncbi.nlm.nih.gov/projects/geo) under ac cession number GSE113617.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo competing interest to declare. However, all data and subsequent analyses were conducted without the use of AI tools, except for AlphaFold 3 sever, which was used for protein model construction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.S. and H.G.W. designed and conceptualized the\u0026nbsp;study and performed data analyses. J.-H.C. and M.J.K. performed data analysis. S.U.M. and M.J.K performed experiments. M.S. J.-H.C. and S.U.M. wrote the manuscript. H.G.W. wrote the manuscript, supervised and funded the study.\u003cstrong\u003e\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eA. Suresh, R. Dhanasekaran, Implications of genetic heterogeneity in hepatocellular cancer, Adv Cancer Res 156 (2022) 103–135.\u003c/li\u003e\n\u003cli\u003ew.b.e. Cancer Genome Atlas Research Network. Electronic address, N. 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Luo, Oncogenic Activity of Solute Carrier Family 45 Member 2 and Alpha-Methylacyl-Coenzyme A Racemase Gene Fusion Is Mediated by Mitogen-Activated Protein Kinase, Hepatol Commun 6(1) (2022) 209–222.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"genomics-and-informatics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Genomics \u0026 Informatics](https://genomicsinform.biomedcentral.com/)","snPcode":"44342","submissionUrl":"https://submission.springernature.com/new-submission/44342/3","title":"Genomics \u0026 Informatics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Fusion gene, HCC, PIWIL2, SLC39A14, Therapeutics-peptides","lastPublishedDoi":"10.21203/rs.3.rs-7217926/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7217926/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFusion genes are key oncogenic drivers in various cancers, yet their role in hepatocellular carcinoma (HCC) remains underexplored. To identify fusion genes contributing to HCC progression, we analyzed RNA-seq data from HCC patients and identified SLC39A14-PIWIL2 as a novel putative driver. Functional assays revealed that the SLC39A14 promoter induces overexpression of a truncated PIWIL2 protein (tPIWIL2), which retains oncogenic MID and PIWI domains. Expression of tPIWIL2 promotes aggressive tumor progression by interacting with oncogenic partners HDAC3 and NME2, as demonstrated through structural modeling and molecular dynamics simulations. To disrupt these interactions, we designed novel decoy peptides that competitively bind PIWIL2 at the HDAC3 and NME2 interfaces, effectively inhibiting tPIWIL2-driven tumor activity in multiple HCC cell lines. Among them, the NEP1 peptide substantially suppressed oncogenic interactions, and its co-administration with 5-Fluorouracil reduced PIWIL2-induced chemoresistance, enhancing therapeutic efficacy. These findings establish SLC39A14-PIWIL2 as a novel oncogenic fusion in HCC and propose fusion protein-targeted peptide therapeutics as a promising strategy for precision treatment in HCC patients.\u003c/p\u003e","manuscriptTitle":"Peptide‑Based Therapeutics Targeting the SLC39A14‑PIWIL2 Fusion in Hepatocellular Carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-14 09:55:39","doi":"10.21203/rs.3.rs-7217926/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-08T10:14:44+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-04T13:12:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-22T05:14:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"192710567991693968176742013021620680544","date":"2025-08-15T03:41:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"137814457923191079351799771948456465200","date":"2025-08-14T09:06:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-07T13:47:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-30T05:02:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-29T06:41:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Genomics \u0026 Informatics","date":"2025-07-26T02:15:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"genomics-and-informatics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Genomics \u0026 Informatics](https://genomicsinform.biomedcentral.com/)","snPcode":"44342","submissionUrl":"https://submission.springernature.com/new-submission/44342/3","title":"Genomics \u0026 Informatics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eb25d4b4-e331-4003-bcc7-a33bf3deefce","owner":[],"postedDate":"August 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-04T04:38:12+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-14 09:55:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7217926","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7217926","identity":"rs-7217926","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}