
==== Front
Transl Oncol
Transl Oncol
Translational Oncology
1936-5233
Neoplasia Press

S1936-5233(24)00175-X
10.1016/j.tranon.2024.102048
102048
Original Research
Therapeutic potential of tLyp-1-EV-shCTCF in inhibiting liver cancer stem cell self-renewal and immune escape via SALL3 modulation in hepatocellular carcinoma
Zhu Heng zh18865900725@126.com
a⁎
Xie Zhihui b
a Department of Gastroenterology, The Fourth People's Hospital of Jinan, No.50, Normal Road, Tianqiao District, Jinan, Shandong Province 250031, P R China
b Department of infectious diseases, Zibo Central Hospital, Zibo 255000, P R China
⁎ Corresponding author. zh18865900725@126.com
25 8 2024
11 2024
25 8 2024
49 1020489 11 2023
12 6 2024
1 7 2024
© 2024 The Authors. Published by Elsevier Inc. CCBYLICENSE.
2024

https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Highlights

• Sparse SALL3 expression in HCC foretells undesirable patient outcomes.

• Boosting SALL3 impedes DNMT3A-facilitated mtDNA methylation and glycolytic adaptations.

• CTCF favors H3K27me3 embellishments, constraining SALL3 output.

• tLyp-1-EV-shCTCF's bolstering of SALL3 offsets metabolic drifts and LCSC's proliferative drive.

• Research insights pioneer groundbreaking HCC management and detection techniques.

The progression of hepatocellular carcinoma (HCC) is influenced by disrupted metabolic processes, presenting challenges in prognostic outcomes. Hepatocellular carcinoma (HCC), a leading cause of cancer-related mortality, is closely associated with metabolic reprogramming and stem cell-like properties in liver cancer stem cells (LCSCs). This study explored the potential molecular mechanisms by which tLyP-1-modified extracellular vesicles (EVs) delivering CTCF shRNA (tLyp-1-EV-shCTCF) regulate mitochondrial DNA methylation-induced glycolytic metabolic reprogramming and LCSC self-renewal. Through a series of methods, including Western blot, nanoparticle tracking analysis, and immunofluorescence, we demonstrated the successful delivery and internalization of tLyp-1-EV in HCC cells. Our results identified SALL3 as a critical factor underexpressed in HCC and LCSCs, while CTCF was overexpressed. Overexpression of SALL3 inhibited LCSC self-renewal and immune evasion by blocking the CTCF-DNMT3A interaction, thus repressing DNMT3A methyltransferase activity and subsequent mitochondrial DNA methylation-mediated glycolytic metabolic reprogramming. In vivo experiments further supported these findings, showing that tLyp-1-EV-shCTCF treatment significantly reduced tumor growth by upregulating SALL3 expression, thereby inhibiting glycolytic metabolic reprogramming and enhancing the immune response against HCC cells. This study provides novel insights into the role of SALL3 and mitochondrial DNA methylation in HCC progression, offering potential therapeutic targets for combating HCC and its stem cell-like properties.

Keywords

Hepatocellular carcinoma
Liver cancer stem cells
Self-renewal
tLyp-1 peptide
Extracellular vesicles
SALL3
DNMT3A
==== Body
pmcIntroduction

Hepatocellular carcinoma (HCC) is among the most prevalent and lethal liver cancers worldwide. The intricate molecular and metabolic landscapes underpinning this disease have rendered its comprehensive elucidation a formidable challenge for the scientific community. This gap in understanding has consequentially impeded the progress in devising effective, targeted therapeutic strategies. Therefore, it is imperative to underscore the importance of an intensified investigation into the molecular dynamics associated with HCC. Such endeavors are crucial for enriching our mechanistic comprehension and enhancing the spectrum of treatment modalities available for this complex condition.

The contribution of cancer stem cells (CSCs), a distinct subset within tumors with self-renewal and differentiation, to the recurrent nature and heterogeneity of HCC is undeniable [1,2]. The immunological backdrop plays a pivotal role in the tumorigenesis of HCC, but the intricate details guiding immune avoidance remain elusive [3]. Fascinatingly, the role of aerobic glycolysis extends to influencing tumor immunity, and metabolic alterations in glycolysis within malignancies can modify the HCC tumor environment [4,5]. Exploration of the mechanisms underlying the CSC characteristics and the reshaping of glycolytic metabolism might usher in innovative strategies for HCC management.

Our examination pinpointed SALL3 as a standout DEG within HCC tissues and LCSCs. Historical research data underscores the promoter hypermethylation of SALL3 and amplified expression across a spectrum of malignancies [6,7]. In a parallel vein, contemporary studies report that hindering SALL3 augments DNA methylation and accentuates cellular proliferation in HCC scenarios [8], with a notable ability to impede the methyltransferase potential of DNMT3A [9]. The interaction of DNMT3A with mtDNA methylation can incite mitochondrial aberrations, potentially steering a course toward glycolytic metabolic alterations [10,11]. Based on the prediction data of this study, CTCF might serve as an antecedent regulator for SALL3. The conjoint action of CTCF with DNMT3A, when affixed to gene promoter zones, could foster enhanced gene methylation and diminished transcriptional activity [12]. Techniques leveraging shRNA to mute CTCF have showcased a retarding effect on HCC tumor evolution and its invasive tendencies [13]. Earlier investigative endeavors have spotlighted the pivotal role of the CUDR-CTCF assembly in modulating LCSCs' malignant transformation [14]. Based on this constellation of insights, we advance the notion that the CTCF-mediated regulation of SALL3 could recalibrate mtDNA methylation-centric metabolic reconfigurations by modulating the functions of DNMT3A, in turn, reshaping HCC cellular core characteristics and immune sidestepping mechanisms.

A plethora of research has demonstrated the capability of extracellular vesicles (EVs) to serve as transporters for shRNA in oncological contexts [15]. An emergent gene therapy tool is the tLyp-1 peptide integrated with EVs, which has shown potential in ferrying siRNA to lung cancer cells [16]. Moreover, when bound to tLyP-1, Mda-7/IL-24 displays cytotoxic effects on liver cancer cells [17]. Our research agenda seeks to elucidate the influence of CTCF on mtDNA methylation-driven alterations in glycolytic metabolism and the self-renewal of LCSCs, examining the SALL3/DNMT3A nexus. We aim to achieve this using an EV-centric shRNA system targeting CTCF, further embellished with the membrane-penetrating peptide tLyP-1, termed tLyP-1-EV-sh-CTCF.

Materials and methods

Ethical approval

The study was conducted under the approval of the Ethics Committee of The Fourth People's Hospital of Jinan, with written informed consent obtained from the participants or their families. All procedures in the animal experiment were conducted in accordance with the Guide for the Care and Use of Laboratory Animals (LL20230021).

Bioinformatics analysis

The HCC-related microarray GSE130666, which carried the platform annotation file GPL15207 and encompassed four control samples and four HCC samples, was procured from the GEO database. Similarly, from the same database, the LCSC-related microarray GSE43503, bearing the platform annotation file GPL6247 and comprising four control samples and four LCSC samples, was retrieved. The differential expression of genes within the microarray samples was analyzed utilizing the "limma" package in R language, adopting |log2FC| > 2 and p < 0.05 as the selection criteria. Subsequently, DEGs were incorporated to construct heat maps using the "pheatmap" package in R language. GEPIA was employed to assess gene expression in HCC, while the association between gene expression and HCC prognosis was evaluated via the Kaplan-Meier Plotter database.

In vitro cell culture and lentiviral infection

The cell lines HEK293T (CL-0005), HepG2 (CL-0103), Hep3B (CL-0102), and Huh7 (CL-0120) were acquired from Procell Life Science & Technology Co., Ltd. (Wuhan, China). Similarly, the HCC cell line SNU-182 (FH0070) and the human normal liver cell line THLE-2 were procured from FuHeng Biology (Shanghai, China).

SNU-182 cells were maintained in RPMI-1640 medium (11,875,119, Gibco, Carlsbad, CA) supplemented with 10 % FBS (10,099,141, Gibco) for culturing conditions. Both HepG2 and Hep3B cells were maintained in MEM (11,095,080, Gibco) enriched with 10 % FBS. The HEK293T and Huh7 cells were grown in DMEM (11,965,092, Gibco), which also contained 10 % FBS. Meanwhile, THLE-2 cells were cultivated in Waymouth medium (31,220,072, Gibco) with 10 % FBS. All cells were placed in an incubator maintained at 37 °C with an atmosphere of 5 % CO2 and 95 % relative humidity. Passaging of the cells was undertaken once the cellular growth density reached approximately 90 %.

For the production of lentiviruses, the overexpression vector pHAGE-CMV-MCS-IRES-ZsGreen (KL-ZL3147) and the assisting vectors pSPAX2 (#12,260) and pMD2.G (#12,259) were co-introduced into 293T cells in tandem with the interference vector pSuper-retro-puro (#87,333) and the auxiliary vectors gag/pol (#14,887) and VSVG (kl-zl-0955). After 48 h of cell cultivation, the supernatant was gathered, centrifugated, and passed through a 0.45 µm filter. An additional virus collection was performed 72 h post-infection, after which it was concentrated via centrifugation. The two isolated viral fractions were amalgamated, and their titer was ascertained. Cells underwent infection with lentiviral vectors encapsulating overexpression (oe)-negative control (NC), oe-SALL3, sh-NC, sh-SALL3–1, or sh-SALL3–2. The shRNA sequences targeting SALL3 were sourced from Sigma-Aldrich (St. Louis, MO; ITRCN0000019754, TRCN0000417790), whereas the sequences aimed at CTCF were conceptualized and synthesized by GenePharma (Shanghai, China), which also undertook the construction of the lentiviral vectors. The sequences were as follows: sh-NC: 5′-CCATTGATGACTCATGCAATT-3′; sh-CTCF-1: 5′-ACGTGTCCACGGCGTTCAAAT-3′; sh-CTCF-2: 5′-CCTCCTGAGGAATCACCTTAA-3′. To devise the pCDNA3.1-HA-tLyp-1-lamp2b vector, the sequence tLyp-1 + lamp2b was integrated into the pCDNA3.1-HA vector (resistant to G418, p29898, procured from MiaoLing Biotechnology, Wuhan, China).

HepG2 and Huh7 cells in the logarithmic growth phase were dissociated using trypsin, and then a cellular suspension at a concentration of 5 × 104 cells/mL was prepared. This suspension was allocated into 6-well plates, introducing 2 mL per well. These plates were then incubated overnight at 37 °C. Post 72 h of lentiviral exposure, the culture medium was substituted with a fresh complete medium that contained either 2 µg/mL puromycin (A1113803, Gibco) or 500 µg/mL G418 (11,811,023, Gibco). This environment was maintained for 5 days to cultivate stably infected cell lines. Subsequently, RT-qPCR analyses were conducted to assess the expression levels of pertinent genes across different cellular groups.

Regarding the co-cultivation of tLyp-1-EVs with HepG2 and Huh7 cells, these cells were initially plated in 6-well plates. When in the logarithmic phase, the cells underwent treatment with 200 µg of tLyp-1-EVs for 48 h. Several treatments were applied: cells either received equivalent volumes of PBS, tLyp-1-EV-sh-NC, or tLyp-1-EV-sh-CTCF; or were infected with sh-NC and subsequently treated with consistent volumes of PBS, tLyp-1-EV-sh-NC, or a combination of tLyp-1-EV-sh-CTCF and sh-NC; or were initially infected with sh-SALL3 and subsequently administered tLyp-1-EV-sh-CTCF.

Flow cytometric sorting

HCC cell specimens were dissociated into single cells using trypsin and subsequently resuspended in PBS enriched with 2 % FBS. They were then treated with PE-labeled CD133 (130–113–670, Miltenyi Biotec, Bergisch Gladbach, Germany) and FITC-labeled CD44 (130–113–334, Miltenyi Biotec) antibodies. Following an hour of incubation shielded from light, they were re-suspended in 0.5 mL of PBS. Post filtration through a nylon mesh, CD44+ CD133+ stem cells were isolated utilizing a flow cytometer (BD Immunocytometry Systems, San Jose, CA) [18].

To assess the proportion of IFN-γ+ CD8+ cells among CD8+ T cells, the T cells were first stimulated using a Cell Activation Cocktail containing Brefeldin A (00–4975–93, Invitrogen, Carlsbad, CA) for 10 h. Subsequently, they were exposed to a CD8-FITC antibody (555,634, BD Biosciences, Franklin Lakes, NJ) for a 20-min duration at 4 °C. These T cells were then fixed and permeabilized following the protocol provided in the Fixation/Permeabilization Solution Kit (#554,714, BD Biosciences). This process was succeeded by a 20-min incubation with an IFNγ-PE antibody (559,327, BD Biosciences) at 4 °C. The final analysis was executed via flow cytometry (BD Immunocytometry Systems) [18,19].

Sphere formation assay

A total of 1 × 103 cells were incubated in serum-deprived medium supplemented with 100 U/mL penicillin, 100 µg/mL streptomycin (15,140,163, Gibco), 20 ng/mL EGF (PHG0311, Gibco), and 20 ng/mL bFGF (13,256–029, Gibco). This incubation was conducted at 37 °C within an incubator, maintaining 5 % CO2. After a 10-day incubation period, the formed spheres were visualized using an inverted microscope (IX73, Olympus, Tokyo, Japan). The spheres were then quantified, and the sphere formation efficiency was determined using the equation: sphere formation rate = (number of spheres per well/initial number of cells seeded in each well) × 100 % [18,20].

EV isolation and extraction

The 293T cells were cultivated in DMEM supplemented with 10 % EV-depleted FBS (EXO-FBS-50A-1, System Biosciences, Palo Alto, CA). Subsequently, the culture supernatant was harvested for EV isolation. This sample was initially centrifuged at 2000 g for 30 min at 4 °C to eliminate cell debris, followed by a 10,000 g centrifugation for 20 min at 4 °C to discard larger vesicles. After passing the supernatant through a 0.22 µm filter, it was subjected to ultracentrifugation at 100,000 g for 60 min at 4 °C. The resulting pellet was reconstituted in PBS for an additional round of ultracentrifugation and then in 100 µL of sterile PBS. This preparation was stored at −20 °C. The tLyp-1-EVs were derived using 293T cells stably transfected with the pCDNA3.1-HA-tLyp-1-lamp2b vector [16].

EV identification

Transmission electron microscopy (TEM) was employed to characterize the morphology and dimensions of the EVs. An aliquot of 30 µL of EVs was deposited onto a copper grid and left for 1 min. Subsequently, the grid was counterstained using 30 µL of phosphotungstic acid solution (pH = 6.8) and allowed to stand at ambient temperature for 5 min. After drying the samples under incandescent lighting, they were examined and imaged via TEM (H-7650, HITACHI, Tokyo, Japan).

The particle size distribution of EVs was assessed using nanoparticle tracking analysis (NTA). Measurements were taken on a Zetasizer Nano-ZS90 device (Malvern Instruments, Malvern, UK), utilizing excitation light at λ = 532 nm. For the analysis, samples were appropriately diluted with 0.15 M NaCl to attain the desired optical signal detection level, specifically at a dilution factor of 1:50 [16].

For the identification of surface markers, a Western blot analysis was conducted. EV precipitates were lysed in RIPA buffer, and protein concentrations were determined using the BCA protein assay kit (20201ES76, Yeasen Company, Shanghai, China). The specific antibodies probed included TSG101, CD63, and CD81, with Calnexin serving as a negative control (Table S1) [16].

Encapsulation of shRNA by EVs

A mixture containing 50 µg of FAM-labeled shRNAs (FAM-shRNAs) and 100 µg of tLyp-1-EVs in 200 µL of electroporation buffer was prepared. This mixture was then subjected to electrotransfection in 96-well plates utilizing an X-porator H1 electroporator (AIDA Pharmaceuticals, Hangzhou, China) set at 400 V. To facilitate the complete recovery of the EV plasma membrane, a subsequent incubation for 30 min at 37 °C was conducted. Extraneous shRNAs were eliminated through ultracentrifugation at 100,000 g for 1 h, with the supernatant subsequently being discarded and the EV precipitate resuspended. The degree of shRNA encapsulation within the EVs was quantified using fluorescence spectrophotometry, employing an emission wavelength of 528 nm and an excitation wavelength of 493 nm [21]. The design and synthesis of the FAM-shRNAs were undertaken by Life Technologies (Thermo Fisher Scientific, Rockford, IL).

To assess stability, tLyp-1-EV-shRNA was incubated with 5 µg/mL RNase A (R1253, Thermo Fisher Scientific) for 30 min at 37 °C. Unencapsulated shRNA served as a reference. Degradation products of the shRNA were then evaluated via polyacrylamide gel electrophoresis and visualized using the Packard InstantImage system.

Immunofluorescence

EVs were labeled following the protocol provided by the PKH26 labeling kit (PKH26GL, Sigma-Aldrich, St. Louis, MO). HCC cells were exposed to 10 µg of PKH26-labeled EVs and incubated for 24 h in a culture dish. After incubation, the cells were fixed using 4 % paraformaldehyde for 30 min. Following this fixation, the cells were detached from the culture dish, permeabilized with 1 % Triton X-100 for 15 min, and then blocked using 2 % BSA for an additional 45 min. After these treatments, the cells were stained with DAPI (2 µg/mL, D9542, Sigma-Aldrich) and sealed. Fluorescence expression was analyzed using an inverted fluorescence microscope (DMI6000B, Leica Microsystems Inc., Buffalo Grove, IL) [22].

mtDNA isolation and methylation detection

Mitochondria were procured from cell specimens following the protocol provided by the mitochondrial isolation kit for cultured cells (89,874, Thermo Fisher Scientific). Approximately 2 × 107 cells were homogenized using 800 µL of cold Reagent A, to which 800 µL of Reagent C was added. Nuclei were sedimented by centrifuging the mixture at 700 g for 10 min. The supernatant was carefully decanted into a fresh tube. Subsequent centrifugation at 12,000 g for 15 min resulted in the sedimentation of mitochondria, which were then resuspended in 500 µL of Reagent C [23].

For mtDNA extraction, the isolated mitochondria were resuspended in a lysis buffer that contained Proteinase K (4,333,793, Invitrogen) and were incubated overnight at 37 °C. This process was followed by mtDNA precipitation using isopropanol and later dissolution in Tris-EDTA buffer. The extent of mtDNA methylation was determined as per the guidelines of the MethylFlash Methylated DNA 5-mC Quantification Kit (P-1034–48, Epigentek, Farmingdale, NY) [24].

Assessment of glucose uptake, lactate content and DNMT3A activity

HCC cells were plated at a density of 2 × 106 cells/well in 6-well culture plates and subsequently incubated at 37 °C for 24 h. Following this, the cells were exposed to the glucose derivative 2-DG for 20 min at 37 °C, in alignment with the guidelines provided by the Glucose Uptake Assay Kit (ab136955, Abcam, Cambridge, UK). This procedure facilitated the assessment of the glucose uptake capability inherent to HCC cells. Concurrently, HCC cells, once again plated at a density of 2 × 106 cells/well in 6-well culture plates, were incubated at 37 °C for 24 h. Post-incubation, the lactate concentration within the HCC cells was ascertained following the protocol of the relevant kit (ab65330, Abcam) [25].

The enzymatic activity of DNMT3A methyltransferase was evaluated. Initially, DNMT3A protein was procured from HCC cell lysates through the utilization of a specific antibody (PA5–77,945, 1:300, Invitrogen), subsequently purified, and quantified using the BCA kit. The DNMT3A methyltransferase activity assessment was conducted in compliance with the instructions of the designated kit (V7601, Promega, Madison, WI). In a concise methodology, 0.5 µg of DNMT3A was incubated alongside 10 µM S-adenosyl methionine and 10 nM ds oligodeoxynucleotide (5′A12-GATCCGACGACGACGACGCGCGCGCGACGACGAGATC, 3 'CTAGGCTGCTGCTGGCGCGCGCGCGCTGCTCTAG-A12) for 60 min at 37 °C, facilitating the enzymatic reaction. This reaction was halted by introducing 1 µL of 0.5 % trifluoroacetic acid. Subsequently, the resultant fluorescence emission was quantified utilizing a Luminescence Microplate Reader [26].

T cell extraction and culture

Fresh peripheral blood was obtained from eight healthy volunteers (aged 25–45 years, without infectious diseases, autoimmune diseases or multiple primary cancers) at The Fourth People's Hospital of Jinan.

To facilitate the isolation of mononuclear cells, this blood was first anticoagulated using heparin, after which a lymphocyte isolation solution (10,771, Sigma-Aldrich) was introduced. After the isolation, cells were resuspended in sterile PBS for enumeration. The CD8+ T cell fraction was then selectively sorted via flow cytometry, employing the CD8-FITC antibody (555,634, BD Biosciences) as the sorting marker.

Post-isolation, CD8+ T cells were cultured in RPMI 1640 medium (A1049101, Gibco) that was supplemented with 10 % FBS (10,099,141, Gibco), 1 % penicillin-streptomycin (15,140,163, Gibco), 2 mM l-glutamine, and 50 µM β-mercaptoethanol (21,985,023, Gibco). This culture was maintained in an incubator at 37 °C with a 5 % CO2 atmosphere.

To activate these T cells, they were exposed to a concoction of PMA and Ionomycin (70-CS1001, MULTI SCIENCES (LIANKE) BIOTECH, Hangzhou, China) and incubated for 2 h at 37 °C. This process was followed by a further incubation of 4 h in the presence of Monensin (5 µg/mL, 70-CS0004, MULTI SCIENCES (LIANKE) BIOTECH) [27,28].

Co-culture of HCC cells with activated CD8+T cells

HCC cells were inoculated in 12-well plates at a density of 5 × 105 cells/well and subsequently cultured overnight in the presence of tLyp-1-EVs. Post incubation, 1 × 105 activated CD8+ T cells were introduced into the apical chambers of the Transwell apparatus (3460, Corning Glass Works, Corning, NY) and the co-culture was sustained for an additional 48 h. Following incubation, T cells were harvested and subjected to flow cytometry for the quantification of the IFN-γ positivity rate. Concurrently, the HCC cells were analyzed for apoptotic markers. The medium from the apical chambers was also collected and subjected to ELISA to gauge the levels of IL-2, using the specific detection kit (RAB0286–1KT, Sigma-Aldrich) that has an assay range between 2.07 pg/mL and 1500 pg/mL [28,29].

Flow cytometric analysis for cell apoptosis

Post co-cultivation, apoptosis in HCC and T cells was assessed using the AnnexinV-FITC/PI dual staining technique. Following co-cultivation, the culture medium was discarded, and the cells were detached using trypsin. Subsequently, these cells were collected in a 15 mL centrifuge tube and centrifuged at 800 g. The supernatant was subsequently removed. Based on the protocols of Apoptosis Assay Kit (556,547, BD Biosciences), cells were resuspended in 500 µL of binding buffer and then combined with a concoction containing 5 µL of FITC and 5 µL of PI. This mixture was incubated in the absence of light for 15 min. The apoptotic status of the cells was then ascertained via flow cytometry using the BD FACSCalibur instrument (Franklin Lakes, NJ) [30,31].

Chromatin immunoprecipitation assay (ChIP)

ChIP assays were conducted as previously described [32]. Briefly, HCC cells were fixed with 1 % formaldehyde for 10 min and lysed. The genome was sonicated to 200 ∼ 1000 bp fragments. Next, 1 µL of CTCF rabbit antibody (MA5–11,187, Invitrogen) and H3K27me3 rabbit antibody (MA5–11,198, Invitrogen) were added to the supernatant in the experimental group and 1 µL of rabbit anti-IgG (ab172730, Abcam) to that in the NC group, followed by incubation with 60 µL of ProteinA Agarose/Salmon Sperm DNA. Finally, precipitants were eluted, and the enriched chromatin fragments were detected using fluorescence PCR [33]. The primer sequence of the SALL3 promoter is detailed in Table S2.

Dual luciferase reporter gene assay and Co-IP assay

The dual luciferase reporter gene vectors, which incorporated the SALL3 promoter, were synthesized and designed by GenePharma. Following transfection of the reporter vector, either with a control vector or the oe-CTCF vector, into HCC cells, the cells were subjected to lysis after a 48-h incubation. Post-transfection, the lysed cells were centrifuged at 12,000 g for 1 min, yielding a supernatant. Luciferase activity was assessed using the Dual-Luciferase® Reporter Assay System (E1910, Promega). A volume of 100 µL of Firefly luciferase working solution was employed to measure Firefly luciferase, while the Renilla luciferase was ascertained with 100 µL of Renilla luciferase working solution. The computed ratio between the Firefly and Renilla luciferase activities represented the definitive luciferase activity [34].

For protein extraction, cells were lysed using an IP lysis buffer composed of specific constituents. Following lysis, cellular debris was separated by centrifugation. Cell lysates underwent an overnight incubation at 4 °C with anti-DNMT3A (PA5–77,945, 1:300, Invitrogen), using IgG (ab172730, Abcam) as a negative control (NC). Subsequently, Protein A/G beads (sc-2003, Santa Cruz Biotechnology) were introduced to the lysates for a 2-h incubation at 4 °C. After thorough washing, these beads were further incubated for 2 h at 4 °C and then subjected to boiling at 100 °C for 5 min. Expressions of CTCF and SALL3 were analyzed via Western blotting [9].

Orthotopic transplanted tumor model in mice

C57BL/6 J mice, aged between 6 and 8 weeks, were procured from Vital River Laboratory Animal Technology Co., Ltd. (Beijing, China). These mice were individually housed in specific-pathogen-free facilities, maintaining a humidity of 60 %−65 % and temperatures ranging from 22 to 25 °C. The conditions also included a 12-h light/dark cycle, and the mice had unrestricted access to food and water. Before experimentation, the mice were allowed a one-week acclimatization period, during which their health was continuously monitored.

Subsequently, these mice were randomly subjected to injections of varying solutions: PBS + sh-NC, tLyp-1-EV-sh-NC + sh-NC, tLyp-1-EV-sh-CTCF + sh-NC, or tLyp-1-EV-sh-CTCF + sh-SALL3 (with n = 6 for each group).

Stably transfected Huh7 cells (sh-NC or sh-SALL3) were dissociated using trypsin, leading to a single-cell suspension of 1 × 106 cells. This suspension was then amalgamated with 1 × 105 CD8+ T cells in 200 µL sterile PBS. This resulting mixture was subsequently introduced subcutaneously into the mice. Following a week from this injection, mice received biweekly tail vein injections of 20 µg tLyp-1-EV-shRNA, while a comparable volume of sterile PBS served as a control. Continuous daily observations were made concerning the overall health of the mice and the tumor inoculation site. Tumor dimensions were recorded every other day, and the volume was computed using the formula: V = (length × width2)/2. After 30 days from the cell injection, the mice were humanely euthanized using an isoflurane respiratory anesthesia system. The emergent subcutaneous tumors were then excised, fixed, and subsequently embedded in paraffin for immunohistochemical studies. After pulverization, fresh tumor tissues were also processed for RT-qPCR analysis and lactate content detection.

Immunohistochemical staining

Tumor tissue samples were fixed in 4 % paraformaldehyde phosphate buffer for 12 h, followed by dewaxing using xylene and hydration through a graded series of alcohol. These tissue samples were then subjected to boiling in a 0.01 M citrate buffer for a period between 15 and 20 min and subsequently blocked with goat serum solution. After the blocking step, the tissue samples were incubated with either CTCF rabbit antibody (MA5–11,187, diluted 1:800, from Invitrogen), SALL3 mouse antibody (sc-271,818, diluted 1:200, from Santa Cruz Biotechnology), or Ki67 rabbit antibody (PA5–19,462, diluted 1:200, from Invitrogen) for 1 h at ambient temperature. Following this, the tissue samples were further incubated with 30 µL of secondary antibodies goat anti-rabbit IgG (ab6721, diluted 1:2000, from Abcam) or goat anti-mouse IgG (ab6729, diluted 1:2000, from Abcam) for an additional hour at room temperature. Thereafter, the samples were treated with streptavidin-peroxidase, allowing for a 30-min incubation at 37 °C. Post this incubation, DAB was employed for color development, lasting between 5 and 10 min. The samples were then counterstained with hematoxylin for 2 min, differentiated using alcohol hydrochloride, and then underwent dehydration, clarification, and sealing. Ultimately, the prepared samples were examined microscopically [35,36].

Detection of lactic acid content in tumor tissue

Tumor tissue samples were gently rinsed with pre-chilled PBS and resuspended in 4–6 × volumes of lactate test buffer. After undergoing fragmentation on ice, the samples were centrifuged at 4 °C for a duration ranging between 2 and 3 min, after which the insoluble fraction was removed. The supernatant, thus obtained, was transferred to a fresh tube. The lactate content in the tumor tissue was subsequently quantified following the protocol provided by the lactate assay kit (ab65330, Abcam) [25].

RT-qPCR and Western blot

Total RNA was isolated from tumor samples utilizing the TRIzol reagent (15,596,018, Invitrogen, Thermo Fisher Scientific), adhering to the protocol recommended by the manufacturer [37]. Subsequently, 1 µg of the isolated RNA underwent reverse transcription to synthesize cDNA, following the procedures delineated by the cDNA reverse transcription kit (4,368,814, Applied Biosystems, Carlsbad, CA). The ViiA 7 fluorescent qPCR System (Life Technologies, Thermo Fisher Scientific) was employed for gene expression analysis. Employing GAPDH as an internal control, gene expression levels were deduced using the 2-ΔΔCt approach. The primers, formulated and produced by Takara (Shiga, Japan), are tabulated in Table S2.

For protein analysis, lysates were prepared employing RIPA buffer and protein concentrations were ascertained with the BCA Protein Assay (20201ES76, Yeasen Company). The lysates were subjected to SDS-PAGE and transferred onto PVDF membranes (IPVH85R, Millipore Corp., Billerica, MA). Following this, the membranes were consecutively incubated with the primary antibodies and either HRP-conjugated goat anti-rabbit IgG (ab6721, Abcam) or goat anti-mouse IgG (ab6789, Abcam) [38]. Quantitative assessment of proteins was achieved using the Image J software (National Institutes of Health), with protein levels normalized against the internal standard, GAPDH or Tubulin [38].

Statistical analysis

Data were analyzed utilizing SPSS 21.0 statistical software (IBM, Armonk, NY). Numerical data were represented as mean ± standard deviation. A t-test was employed for comparisons between two groups. A one-way ANOVA was performed for comparisons across multiple groups, followed by the Tukey post hoc test. A repeated measures ANOVA was executed for data among multiple groups and different time intervals, followed by the Tukey post hoc test. A p-value less than 0.05 indicated statistical significance.

Results

Downregulated SALL3 in HCC tissues and LCSCs was associated with poor prognosis in HCC patients

We first obtained 834 and 36 differentially expressed genes, respectively, after differential analysis of GEO datasets (GSE130666, GSE43503) (Fig. 1A, B), respectively, and SALL3 was significantly under-expressed in HCC tissues and LCSCs (Fig. 1C, D). In addition, GEPIA database analysis showed that SALL3 expression was correlated with overall survival in HCC patients (Fig. 1E).Fig. 1 Bioinformatics prediction and in vitro experiment to validate SALL3 expression in HCC cells and LCSCs. A, Volcano plot of expression of DEGs in microarray GSE130666 (Red color represents up-regulation, green color represents down-regulation, and black color represents no change). B, Volcano plot of expression of DEGs in microarray GSE43503 (Red color represents up-regulation, green color represents down-regulation, and black color represents no change). C, Box plot of SALL3 gene expression in microarray GSE130666. The grey color represents normal samples (n = 4), and the blue color represents HCC samples (n = 4). D, Box plot of SALL3 expression in microarray GSE43503. The grey color represents normal samples (n = 4), and the blue color represents LCSC samples (n = 4). E, Survival curves of the prognosis of SALL3 in patients with HCC analyzed using the GEPIA website. Based on the median gene expression, HCC patients who underwent resection with follow-up data recorded were divided into two groups (high and low expression groups), with red indicating high expression and black indicating low expression. F, RT-qPCR to detect SALL3 expression in HCC cell lines (SNU-182, HepG2, Hep3B and Huh7) and immortalized human hepatocyte line (L02). * p < 0.05 vs. L02 cells. G. Western blot detection of SALL3 expression in HCC cell lines (SNU-182, HepG2, Hep3B and Huh7) and immortalized human hepatocyte lines (L02). * p < 0.05 vs. L02 cells. H, Flow cytometry (FACS) to sort CD44+ CD133+ cells in HepG2 and Huh7 cell lines. I. Flow cytometry detection of the proportion of CD44+ CD133+ cells in the CD44+ CD133+ populations obtained by FACS sorting. J, RT-qPCR detection of SALL3 expression in CD144+ CD133+ and CD44− CD133− cells after FACS sorting of HCC cell lines. * p < 0.05 vs. CD44− CD133− cells. K, RT-qPCR to detect SALL3 expression in sphere-forming cells. * p < 0.05 vs. parental cells. All cell experiments were repeated three times.

Fig 1

To investigate the expression of SALL3 in LCSCs, we first examined the expression of SALL3 in HCC cell lines (SNU-182, HepG2, Hep3B and Huh7) and immortalized human hepatocyte cell line (L02). The results showed that the expression of SALL3 was markedly lower in the four HCC cell lines than in the L02 cell line, and that among the HCC cell lines, SALL3 showed the lowest expression in the HepG2 and Huh7 cell lines. Therefore, HepG2 and Huh7 cell lines were chosen for the follow-up experiment (Fig. 1F, G).

Next, we used the fluorescence-activated cell sorting (FACS) method to isolate CD44+ CD133+ LCSCs from HepG2 and Huh7 cell lines using the specific markers CD133 and CD44 on the surface of LCSCs (Fig. 1H). Flow cytometry results showed that the FACS method successfully sorted the CD44+ CD133+ cell populations in each cell line with a double positive rate of over 90 % for both CD133 and CD44 (Fig. 1I). RT-qPCR results also showed that SALL3 was less expressed in CD44+ CD133+ cells than in CD44− CD133− cells (Fig. 1J). In addition, we enriched LCSCs by sphere formation assay and found lower expression of SALL3 in sphere-forming cells through RT-qPCR (Fig. 1K).

The above results suggested the underexpression of SALL3 in HCC tissues and LCSCs and the correlation of downregulated SALL3 with poor prognosis in HCC patients.

Overexpression of SALL3 repressed immune escape of HCC cells

To investigate the effect of SALL3 on HCC, we overexpressed SALL3 in HepG2 and Huh7 cells. As shown in Fig. 2A, B, oe-SALL3 increased the expression of SALL3 in HepG2 and Huh7 cells, while the expression of stemness-related transcription factors (Oct4, SOX2, Nanog and BMI-1) was significantly decreased. We also found that overexpression of SALL3 reduced the proportion of CD44+ CD133+ cells and sphere-forming ability in HCC cells (Fig. 2C, D).Fig. 2 Effects of overexpression of SALL3 on stemness and immune escape of HCC cells. A, RT-qPCR to detect the mRNA level of related genes in HCC cells overexpressing SALL3. B, Western blot to detect the protein expression of related genes in HCC cells overexpressing SALL3. C, Flow cytometry to detect the proportion of CD44+ CD133+− cells in HCC cells overexpressing SALL3. D, Sphere-forming images and sphere-forming rate after two weeks of sphere-forming culture in HCC cells overexpressing SALL3. E, Flow cytometry to detect the proportion of IFN-γ+ CD8+T cells in CD8+T cells after HCC cells were co-cultured with activated CD8+T cells. F, ELISA to detect the amount of IL-2 in the co-culture medium after HCC cells were co-cultured with activated CD8+T cells. G, Annexin V/PI staining to detect the apoptotic rate of HCC cells after HCC cells were co-cultured with activated CD8+T cells. * p < 0.05 vs. the oe-NC group. All cell experiments were repeated three times.

Fig 2

Next, to investigate the effect of SALL3 on the immune escape of HCC cells, we used HepG2 and Huh7 cells to co-culture with activated CD8+ T cells. As shown in Fig. 2E-G, the proportion of IFN-γ+ CD8+ T cells was significantly increased in the presence of SALL3 overexpression (Fig. 2E), accompanied by marked increases in the level of IL-2 in the culture medium and in the apoptotic rate of HCC cells (Fig. 2F, G). Overall, overexpressed SALL3 could repress immune escape of HCC cells.

Overexpression of SALL3 inhibited DNMT3A activity and suppressed reprogramming of glycolytic metabolism in HCC cells

To explore the downstream regulatory mechanism of SALL3, we predicted the downstream regulators of SALL3 using the STRING tool and found a reciprocal relationship between SALL3 and DNMT3A (Fig. 3A).Fig. 3 Overexpression of SALL3 inhibits reprogramming of glycolytic metabolism in HCC through DNMT3A-mediated mtDNA methylation. A, Gene interaction network of SALL3. B, Co-IP detection of the interaction of SALL3 with DNMT3A, CTCF and DNMT3A in HCC cells. C, Methyltransferase activity of DNMT3A in HCC cells overexpressing SALL3. D, ELISA detection of the methylation level of mtDNA in HCC cells overexpressing SALL3. E, Glucose uptake capacity of HCC cells overexpressing SALL3. F, Lactate production of HCC cells overexpressing SALL3. G, RT-qPCR to detect the expression of related genes of HCC cells overexpressing SALL3. * p < 0.05 vs. the oe-NC group. All cell experiments were repeated three times.

Fig 3

Co-IP assay results showed that the interaction between SALL3 and DNMT3A in HCC cells was enhanced after overexpression of SALL3, while the interaction between CTCF and DNMT3A was weakened (Fig. 3B). Also, we found that overexpression of SALL3 inhibited the methyltransferase activity of DNMT3A (Fig. 3C). As shown in Fig. 3D, the methylation level of mtDNA in HCC cells was significantly decreased after overexpression of SALL3.

We then examined the level of reprogramming of glycolytic metabolism in HCC cells. As shown in Fig. 3E, F, glucose uptake and lactate production were significantly inhibited in the HCC cells overexpressing SALL3, and mRNA levels of genes related to reprogramming of glycolytic metabolism (SCL2A1, HK2, PFKL and LDHA) were also significantly reduced (Fig. 3G).

Taken together, overexpressed SALL3 could inhibit DNMT3A activity to suppress reprogramming of glycolytic metabolism in HCC cells.

CTCF acted as a transcription factor to repress SALL3 expression by promoting H3K27me3 modification on the SALL3 promoter

To explore the upstream regulatory mechanism of SALL3, we first predicted the upstream transcription factors of SALL3 through the hTFtarget database and found that nine transcription factors were expressed in liver tissues, namely CTCF, CTCF, CTCF, FOXA2, GABPA, RAD21, SMC3, STAG1 and USF1, among which in the TSS region the transcription factors with peaks present were CTCF, FOXA2 and USF1 (Table S3).

The TCGA database-based differential analysis revealed that CTCF was significantly highly expressed in HCC (Fig. 4A). We then found that CTCF was significantly highly expressed in HCC cell lines compared to that in the immortalized human hepatocyte line (L02) (Fig. 4B, C). In addition, we also found that CTCF was highly expressed in CD44+ CD133+ LCSCs relative to that in the CD44− CD133− HCC cells (Fig. 4D). Moreover, CTCF expression was also markedly increased in sphere-forming cells (Fig. 4E).Fig. 4 Transcription factor CTCF inhibits SALL3 expression in HCC and LCSCs. A, CTCF expression in HCC liver cancer tissues (n = 374) and normal samples (n = 50) obtained by TCGA database (Red color represents the tumor group, and grey color represents the normal group). B, RT-qPCR detection of CTCF in HCC cell lines (SNU-182, HepG2, Hep3B and Huh7) and immortalized human hepatocyte line (L02), * p < 0.05 vs. L02 cells. C, Western blot to detect CTCF expression in HCC cell lines (SNU-182, HepG2, Hep3B and Huh7) and immortalized human hepatocyte line (L02). * p < 0.05 vs. L02 cells. D, RT-qPCR to detect CTCF expression in CD144+ CD133+ and CD44− CD133− cells after FACS sorting. * p < 0.05 vs. CD44− CD133− cells. E, RT-qPCR to detect CTCF expression in sphere-forming cells. * p < 0.05 vs. parental cells. F, RT-qPCR to detect CTCF expression in HCC cells. * p < 0.05 vs. sh-NC. G & H, ChIP assay for the enrichment of CTCF protein (G) and H3K27me3 (H) on SALL3 promoter in HCC cells. * p < 0.05 vs. IgG group. I, Dual-luciferase reporter gene assay to detect SALL3 promoter activity. * p < 0.05 vs. sh-NC group. J, RT-qPCR to determine SALL3 expression in HCC cells. * p < 0.05 vs. sh-NC group. All cell experiments were repeated three times.

Fig 4

Next, we knocked down CTCF in cells and performed RT-qPCR to verify the effect. Both shRNA sequences significantly inhibited CTCF expression, with sh-CTCF-1 being more effective and, therefore, used in subsequent experiments (Fig. 4F). As shown in Fig. 4G, H, the knockdown of CTCF inhibited the enrichment of CTCF protein and H3K27me3 on the SALL3 promoter. Further dual luciferase reporter gene assay showed that knockdown of CTCF promoted SALL3 promoter activity (Fig. 4I). RT-qPCR assays revealed that SALL3 expression was decreased in HCC cells with CTCF knockdown (Fig. 4J).

The above results indicated that CTCF was highly expressed in both HCC cells and LCSCs and that CTCF could act as a transcription factor to repress SALL3 expression by promoting H3K27me3 modification on the SALL3 promoter.

Successful preparation of shRNA-loaded tLyp-1-EVs

To construct an engineered EV targeting CTCF, we transfected 293T cells with the HA-labeled tLyp-1-Lamp2b vector to construct a stable transfection line. RT-qPCR and Western blot showed that the expression of Lamp2b was significantly increased in the transfected 293T cells compared to that in the untransfected cells (Fig. 5A), with the presence of HA expression (Fig. 5B), which indicated that the transfection was successful.Fig. 5 tLyp-1-EV-shRNA construction and identification. A, RT-qPCR to detect the mRNA level of Lamp2b in 293T cells. * p < 0.05 vs. control group. B, Western blot to detect the HA expression in 293T cells. * p < 0.05 vs. control group. C, TEM to observe the ultrastructure of EV. D, Western blot to detect the expression of EV surface marker proteins. E, NTA to determine the size distribution of EVs. F, Western blot to detect the expression of HA on EVs. G, Flow cytometry to detect the fluorescence intensity of PKH67 in HCC cells, FL1-H: Fluorescence 1 Height. H, Schematic diagram of the procedure of shRNA loading of EVs. I, The tLyp-1-EV-shRNA and shRNA were treated with RNase A, and the hydrolysis products were detected using polyacrylamide gels. J, Fluorescence microscopy for observation of HCC cells. K & L, RT-qPCR to detect gene expression of CTCF (K) and SALL3 (L) in HCC cells. All cell experiments were repeated three times.

Fig 5

Next, we isolated and identified EVs from culture supernatants of transfected or untransfected 293T cells by ultracentrifugation. The isolated vesicles were observed by TEM, which presented round and elliptical membranous vesicle discs with intact envelopes and similar morphology, with diameters ranging from 40 to 100 nm (Fig. 5C, D). NTA showed that the major vesicle sizes ranged from 50 to 200 nm (Fig. 5E). In addition, the Western blot assay displayed that only tLyp-1-EVs expressed HA (Fig. 5F). After co-culture with PKH67-labeled EVs in HCC cells, flow cytometry revealed that the uptake of tLyp-1-EVs by HCC cells was significantly higher than that of natural EVs (Fig. 5G). These results indicated that tLyp-1-EVs extraction was successful.

We then encapsulated the FAM-labeled shRNA into tLyp-1-EVs by electroporation (Fig. 5H). After co-culture with RNase A, the naked shRNA was completely degraded, while the shRNA loaded in tLyp-1-EVs was largely undegraded (Fig. 5I). This finding suggested that EV had a role in sequestering and protecting shRNA. tLyp-1-EV-shRNA co-cultured with HCC cells showed co-localization of PKH67-labeled EVs with FAM-labeled shRNA in HCC cells under fluorescence microscopy (Fig. 5J). Further RT-qPCR results revealed that CTCF expression decreased and SALL3 expression increased in HCC cells with the addition of tLyp-1-EV-sh-CTCF relative to that in HCC cells treated with tLyp-1-EVs, while there was no significant difference between the HCC cells treated with PBS and those treated with tLyp-1-EVs (Fig. 5K-L). The above results indicated that we successfully constructed tLyp-1-EV-shRNA.

tLyp-1-EV-sh-CTCF inhibited mtDNA methylation-mediated reprogramming of glycolytic metabolism and self-renewal of LCSCs through upregulation of SALL3 expression

To investigate the effect of tLyp-1-EV- sh-CTCF regulating SALL3 expression on HCC cells, we designed shRNA sequences of SALL3 and then transfected them into HCC cells. RT-qPCR results showed that both shRNA sequences significantly inhibited the expression of SALL3, and sh-SALL3–1 with optimal efficacy was selected for subsequent experiments (Fig. 6A).Fig. 6 Effects of tLyp-1-EV-sh-CTCF on HCC cells by regulating SALL3 expression. A, RT-qPCR to detect the mRNA level of SALL3 in HCC cells after treatment with sh-SALL3–1 or sh-SALL3–2. B, Methyltransferase activity of DNMT3A in HCC cells. C, ELISA to detect the methylation level of mtDNA in HCC cells. D, Glucose uptake ability of HCC cells. E, Lactate production in HCC cells. F & G, RT-qPCR to detect the mRNA expression of stemness-related genes in HCC cells. H, Western blot to detect the protein level of stemness-related genes in HCC cells. I, Flow cytometry to detect the proportion of CD44+ CD133+− cells in HCC cells. J, Images of cell sphere-forming and statistical graph of sphere-forming rate after two weeks of sphere-forming culture of HCC cells. K-M, After HCC cells were co-cultured with activated CD8+T cells, the proportion of IFN-γ+ CD8+T cells in CD8+T cells was detected by flow cytometry (K), the amount of IL-2 in the co-culture medium was detected by ELISA (L) and the apoptotic rate of HCC was detected by Annexin V/PI staining (M). * p < 0.05 vs. tLyp-1-EV-sh-NC + sh-NC group. # p < 0.05 vs. tLyp-1-EV-sh-CTCF + sh-NC group. All cell experiments were repeated three times.

Fig 6

We co-cultured HCC cells with EVs, and RT-qPCR assays showed that CTCF expression decreased and SALL3 expression increased in HCC cells treated with tLyp-1-EV-sh-CTCF relative to those in HCC cells treated with tLyp-1-EVs, while additional treatment of sh-SALL3 failed to change CTCF expression but it reduced SALL3 expression (Fig. 2G).

As shown in Fig. 6B, C, the methyltransferase activity and mtDNA methylation levels of DNMT3A were significantly decreased in HCC cells treated with tLyp-1-EV-sh-CTCF relative to those in HCC cells treated with tLyp-1-EVs, while additional SALL3 knockdown could reverse the trends. We also found that relative to those in HCC cells in response to tLyp-1-EVs, the glucose uptake and lactate production ability of HCC cells in response to tLyp-1-EV-sh-CTCF were markedly inhibited, and the mRNA levels of genes related to reprogramming of glycolytic metabolism were significantly reduced; the above trends could be negated by additional SALL3 knockdown (Fig. 6D-F).

Next, we examined the stemness and immune escape of HCC cells, as shown in Fig. 6G-J. The expression of stemness-related transcription factors, the proportion of CD44+ CD133+ cells and sphere-forming ability in HCC cells were significantly reduced by tLyp-1-EV-sh-CTCF, while additional SALL3 knockdown counteracted the effect. In addition, the proportion of IFN-γ+ CD8+ T cells in CD8+ T cells co-cultured with tLyp-1-EV-sh-CTCF was significantly increased relative to that in CD8+ T cells co-cultured with tLyp-1-EVs (Fig. 6K), as were the increased levels of IL-2 in the co-culture medium and the elevated apoptotic rate in HCC cells (Fig. 6L, M). SALL3 knockdown could reverse the increased proportion of IFN-γ+ CD8+ T cells in CD8+ T cells co-cultured with tLyp-1-EV-sh-CTCF (Fig. 6J) and abrogate the elevated level of IL-2 in the co-culture medium and the increased apoptotic rate of HCC cells (Fig. 6 L-M). In addition, there was no significant difference in the indicators mentioned above between HCC cells treated with PBS and those treated with tLyp-1-EVs.

Collectively, tLyp-1-EV-sh-CTCF could upregulate SALL3 expression, thereby inhibiting mtDNA methylation-mediated reprogramming of glycolytic metabolism and self-renewal of LCSCs.

tLyp-1-EV-sh-CTCF inhibited tumorigenesis and reprogramming of glycolytic metabolism of HCC cells in mice through upregulation of SALL3 expression

To investigate the effect of tLyp-1-EV-sh-CTCF regulation of SALL3 expression on HCC cell tumorigenesis in vivo, we injected a mixture of stably transduced Huh7 cells and CD8+ T cells subcutaneously into mice and then treated mice with EVs. As shown in Fig. 7A-C, relative to the mice treated with tLyp-1-EVs, those treated with tLyp-1-EV-sh-CTCF had notably reduced growth rate and volume of subcutaneous tumors. In contrast, relative to the mice treated with tLyp-1-EV-sh-CTCF, those treated with tLyp-1-EV-sh-CTCF + sh-SALL3 increased growth rate and volume of subcutaneous tumors.Fig. 7 Effects of tLyp-1-EV-sh-CTCF on tumorigenic capacity and reprogramming of glycolytic metabolism in HCC cells in mice by regulating SALL3 expression. Mice were injected with tLyp-1-EV-sh-CTCF or tLyp-1-EV-sh-CTCF + sh-SALL3. A, Images of subcutaneously transplanted tumors in mice. B, Change curve of the volume of subcutaneously transplanted tumors in mice. C, Weight of subcutaneously transplanted tumors in mice. D, Immunohistochemical detection of expression of CTCF, SALL3 and Ki67 in subcutaneously transplanted tumors in mice. E & F, RT-qPCR detection of relevant gene expression in subcutaneously transplanted tumors in mice. G, Lactic acid production in subcutaneously transplanted tumors in mice. n = 6. * p < 0.05 vs. tLyp-1-EV-sh-NC + sh-NC group. # p < 0.05 vs. tLyp-1-EV-sh-CTCF + sh-NC group.

Fig 7

Immunohistochemical results demonstrated that relative to tLyp-1-EVs, tLyp-1-EV-sh-CTCF resulted in declines in the expression of CTCF and proliferation marker Ki67 and an increase in the expression of SALL3 in the tumor tissues of mice, which could be reversed by additional treatment with sh-SALL3 (Fig. 7D).

In addition, mRNA levels of stemness-related genes and reprogramming of glycolytic metabolism-related genes were significantly reduced in the tumors in mice in the presence of tLyp-1-EV-sh-CTCF (Fig. 7E-F), accompanied by suppressed lactate production capacity (Fig. 7G). In contrast, the mRNA levels of stemness-related genes and glycolytic reprogramming-related genes in the tumors in mice were notably increased in the presence of tLyp-1-EV-sh-CTCF + sh-SALL3 compared to that upon tLyp-1-EV-sh-CTCF (Fig. 7E-F), with increased lactate production (Fig. 7G).

These results suggested the inhibitory role of tLyp-1-EV-sh-CTCF in tumorigenesis and reprogramming of glycolytic metabolism of HCC cells in mice through upregulation of SALL3 expression.

Discussion

HCC presents a formidable challenge in oncology, largely due to its complex molecular basis. Recent advances highlight the revolutionary role of EVs in facilitating intercellular communication, particularly in cancer treatment. The integration of targeted peptides, exemplified by the tLyp-1-EV-sh-CTCF system, into Evs, opens new avenues for precision medicine. Meanwhile, the transcription factor CTCF has emerged as a key player in altering the genomic landscape and regulating gene expression in HCC. The critical task ahead involves disentangling the complex relationship between CTCF, glycolytic metabolic reprogramming, and the unique self-renewal capabilities of LCSCs, offering promising directions for therapeutic intervention.

Our investigation has elucidated that SALL3 exhibits significant underexpression in both HCC tissues and LCSCs, with its enhanced expression potentially mitigating immune evasion mechanisms within HCC cells. Notably, SALL family members have been implicated in facilitating the infiltration of immune cells [39]. Corroborating our findings, previous studies have documented markedly lower levels of SALL3 mRNA in tumor tissues of HCC patients compared to adjacent non-tumor tissues, a phenomenon attributed to the hypermethylation of promoter CpG islands [8]. Further, an in-depth analysis incorporating genomic, epigenomic, and transcriptomic data from HCC tissues identified significant methylation alterations associated with SALL3 in early-stage HCC, suggesting a substantial decrease in SALL3 protein expression [40]. Our research contributes to this body of knowledge by demonstrating that such genomic hypermethylation markedly suppresses SALL3 expression, crucial for regulating LCSCs.

In vitro assays conducted as part of our study revealed that overexpression of SALL3 leads to a reduction in DNMT3A activity, thereby obstructing the glycolytic metabolic reprogramming in HCC cells. This observation is in harmony with recent findings demonstrating the interaction of SALL3 with DNMT3A through its double zinc finger configuration, directly interplaying with the PWWP domain of DNMT3A to inhibit its activity [9]. Similar mechanisms involving stilbenoid-induced upregulation of SALL3 have been observed to sequester DNMT3A in breast cancer cells [7]. Beyond the recognition of SALL3 molecular signals by DNMT3A, its involvement in epigenetic modifications that regulate glucose metabolism has been well-documented [41]. Moreover, our analyses have delineated the role of CTCF in repressing SALL3 expression through the enhancement of H3K27me3 modifications at the SALL3 promoter site. CTCF, characterized by its conserved zinc finger domains, is pivotal in regulating the transcription of numerous proteins, interacting with specific genomic loci to modulate activity via H3K27me3 modifications [42]. Reductions in CTCF have been shown to decrease H3K27me3 levels at the RB1 promoter, leading to reduced pRB expression and facilitating tumorigenesis [43]. Thus, the CTCF-induced modulation of H3K27me3 modifications likely influences the expression of a wide array of genes, contributing to the pathogenesis of HCC.

Additionally, our findings unveiled that tLyp-1-EV-sh-CTCF curbed mtDNA methylation-induced glycolytic metabolic reprogramming and the in vitro self-renewal of LCSCs, along with in vivo HCC cell tumorigenesis, via enhanced SALL3 expression. Several studies have demonstrated the success of multiple targeting peptides in pinpointing specific cancer cells through modifications of exosomes targeting said cells [44]. Fusion of exosomal proteins with peptide ligands and the capacity of EVs to ferry siRNA into mouse brains is notable [45], and modified targeting tLyp-1 EVs show promise in siRNA delivery targeting lung cancer cells for oncogenic suppression [16]. Interestingly, tLyP-1-Ps-siNAC-1 has been spotlighted for boosting metastatic triple-negative breast cancer chemotherapy, a cancer type influenced by CSC accumulation [46]. Furthermore, CTCF elevation in primary HCC vis-a-vis non-tumorous livers is significant [13]. Evidence suggests that CTCF knockdown diminishes EZH2 binding and modifies SOCS3 promoter methylation in HCC [47]. The unveiling of the CUDR-CTCF assembly underscored its role in dictating LCSCs' malignant differentiation [14]. Notably, the influence of CTCF on aerobic glycolysis has been documented in the context of neuroblastoma [48]. Yet, prior research hasn't incorporated CTCF into a tLyp-1-EV-centric delivery framework.

To summarize, tLyp-1-EV-sh-CTCF fosters the augmentation of SALL3 expression, concurrently impeding DNMT3A methyltransferase function by attenuating H3K27me3 modification linked with the SALL3 promoter. Such alterations effectively halt the mtDNA methylation-driven reprogramming of glycolytic metabolism, thereby impairing the self-renewal capabilities of LCSCs and circumventing the immune evasion strategies of HCC (Fig. 8). Our findings suggest that the targeted neutralization of CTCF by tumor-directed EVs can significantly alter the metabolic trajectory of tumor cells. Nonetheless, considering the functional role of the transcription factor CTCF in gene expression governance and genomic alteration in tumor cells, along with its extensive influence on a myriad of regulated genes, it is conceivable that alternative compensatory mechanisms may come into play. The potential for CTCF-mediated regulatory mechanisms to recur across different tumor types also presents a fertile ground for further research.Fig. 8 Molecular mechanism of tLyp-1-EV-sh-CTCF in regulating mtDNA methylation-induced reprogramming of glycolytic metabolism and self-renewal of LCSCs. tLyp-1-EV-sh-CTCF upregulates SALL3 expression and inhibits DNMT3A methyltransferase activity by suppressing H3K27me3 modification of the SALL3 promoter, inhibiting mtDNA methylation-induced reprogramming of glycolytic metabolism, thereby repressing self-renewal of LCSCs and HCC immune escape.

Fig 8

The clinical translation of tLyp-1-modified EVs faces challenges, notably the variability in therapeutic responses owing to genetic diversity among patients, and the imperative for extended studies to ascertain the long-term stability of the treatment outcomes. Recognizing these hurdles, we underscore the necessity for clinical trials to validate our findings in a diverse patient population. Further exploration into the mechanism of action in varied genetic backgrounds and the exploration of synergistic therapies to augment efficacy represent vital avenues for subsequent investigations. By integrating these discussions into our manuscript, we aim to acknowledge the constraints of our current study while laying the groundwork for future endeavors that can build on our preliminary insights, ultimately advancing the understanding and treatment of HCC.

Ethics approval and consent to participate

The study was conducted under the approval of the Ethics Committee of The Fourth People's Hospital of Jinan, with written informed consent obtained from the participants or their families. All procedures in the animal experiment were conducted in accordance with the Guide for the Care and Use of Laboratory Animals (LL20230021).

Funding

Not applicable.

Consent for publication

Not applicable.

Availability of data and materials

The data that supports the findings of this study are available on request from the corresponding author upon reasonable request.

CRediT authorship contribution statement

Heng Zhu: Writing – review & editing, Writing – original draft, Formal analysis. Zhihui Xie: Writing – review & editing, Supervision, Software.

Declaration of competing interest

The authors declare that they have no competing interests.

Appendix Supplementary materials

Image, application 1

Image, application 2

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Image, application 4

Acknowledgments

Not applicable.

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.tranon.2024.102048.
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