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Article
The Vault Complex Is Significantly Involved in Therapeutic Responsiveness of Endocrine Tumors and Linked to Autophagy under Chemotherapeutic Conditions
Stefan Bornstein 1,2,+, Igor Shapiro 1,+, Alekhya Mazumdar 3,4(D, Kathrin Zitzmann 5, Svenja Nölting 1,5, Edlira Luca 1D, Felix Beuschlein 10, Ashish Sharma 1 and Constanze Hantel 1,2,*
1 Department of Endocrinology, Diabetology and Clinical Nutrition, University Hospital Zurich (USZ) and University of Zurich (UZH), 8091 Zurich, Switzerland
2 Medizinische Klinik Und Poliklinik III, University Hospital Carl Gustav Carus Dresden, 01307 Dresden, Germany
3 Department of Orthopedics, Balgrist University Hospital, 8008 Zurich, Switzerland
4 Department of Urology, University Hospital Zurich (USZ) and University of Zurich (UZH), 8091 Zurich, Switzerland
5 Department of Medicine IV, University Hospital, LMU Munich, 80336 Munich, Germany
* Correspondence: constanze.hantel@usz.ch; Tel .: +41-43-253-3008
+ These authors contributed equally to this work.
☒ check for updates
Citation: Bornstein, S .; Shapiro, I .; Mazumdar, A .; Zitzmann, K .; Nölting, S .; Luca, E .; Beuschlein, F .; Sharma, A .; Hantel, C. The Vault Complex Is Significantly Involved in Therapeutic Responsiveness of Endocrine Tumors and Linked to Autophagy under Chemotherapeutic Conditions. Cancers 2023, 15, 1783.
https://doi.org/10.3390/ cancers15061783
Academic Editor: Guido Rindi
Received: 20 February 2023
Revised: 10 March 2023
Accepted: 13 March 2023
Published: 15 March 2023
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Copyright: @ 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Simple Summary: The vault complex, consisting of a major vault protein (MVP), two minor vault proteins (VPARP and TEP1), and small untranslated vault RNA molecules, is considered the largest intracellular ribonucleoprotein particle. Although in recent years vaults were believed to be involved in multidrug resistance (MDR), the exact function of this complex has remained unclear. Our findings reveal a so far unexplored role of the vault complex that is closely linked to the therapeutic responsiveness of endocrine tumors.
Abstract: Cancers display dynamic interactions with their complex microenvironments that influence tumor growth, invasiveness, and immune evasion, thereby also influencing potential resistance to therapeutic treatments. The tumor microenvironment (TME) includes cells of the immune system, the extracellular matrix, blood vessels, and other cell types, such as fibroblasts or adipocytes. Various cell types forming this TME secrete exosomes, and molecules thereby released into the TME have been shown to be important mediators of cellular communication and interplay. Specific stressors in the TME, such as hypoxia, starvation, inflammation, and damage, can furthermore induce autophagy, a fundamental cellular process that degrades and recycles molecules and subcellular components, and recently it has been demonstrated that the small non-coding vault RNA1-1 plays a role as a regulator of autophagy and the coordinated lysosomal expression and regulation (CLEAR) network. Here, we demonstrate for the first time that intra-tumoral damage following effective therapeutic treatment is linked to specific intracellular synthesis and subsequent exosomal release of vault RNAs in endocrine tumors in vitro and in vivo. While we observed a subsequent upregulation of autophagic markers under classical chemotherapeutic conditions, a downregulation of autophagy could be detected under conditions strongly involving inflammatory cascades.
Keywords: autophagy; vault RNA; vault complex; MVP; VPARP; TEP-1; NCI-H295; BON; adrenocortical carcinoma; neuroendocrine tumor; endocrine tumor; EDPM; TNF alpha
1. Introduction
Autophagy is a tightly regulated, catabolic process required for physiological cell homeostasis. It is defined as the fusion of autophagic vacuoles with lysosomes leading to autophagolysosome formation, including subsequent digestion and recycling of cellular
components. Activated by specific autophagy-related genes (ATGs), it is induced in re- sponse to different stimuli, such as starvation and oxidative stress. In addition, autophagy is of particular importance in cancer where it plays a dual role leading to cytoprotective or cytotoxic effects [1]. Thus, appropriate autophagy modulations could also bare potential for therapeutic strategies against cancer [1,2]. The regulation of autophagy in cancer has been described in response to cytokines, which are related to immune system activation and the immunosuppressive tumor microenvironment (TME); its specific role in this con- text, however, appears to be highly complex and divergent. Overall, it is known that the regulation of autophagy can influence tumor immunity, suppress the adaptive immune response, and thereby also affect immunotherapies in many ways [3].
An important key player in autophagic flux is the ATG12-ATG5/ATG16 complex, within which ATG5 is indispensable and involved in both canonical and non-canonical autophagy processes. Similarly, LC3BI/II as well as lysosome associated membrane pro- teins (LAMP1, LAMP2), among others, have been defined as further key factors involved in autophagy. Moreover, long non-coding RNAs and microRNAs have also been shown to modulate autophagy [1,2,4-6]. Most recently, the small non-coding vault RNA1-1 has been demonstrated to act as a riboregulator of autophagy and lysosome-mediated chemotherapy resistance [7-10].
Vault particles are the largest ribonucleoprotein complexes identified to date. Bigger than ribosomes and with potential copy numbers of up to 100,000 per cell, vault particles are abundantly expressed and furthermore highly conserved across organisms [10]. The gigantic cellular complex consists of the major vault protein (MVP, accounting for more than 70% of the particle mass and capable of reversible self-assembly [10,11]), vault poly (ADP-ribose) polymerase (VPARP), telomerase-associated protein-1 (TEP1), and the above- mentioned small non-coding vault RNAs (1-1, 1-2, 1-3, and 2-1) from which ~4.6% are directly associated with the particle while the rest is of cytoplasmic localization [12,13]. However, the exact cellular function of these large and cellular highly abundant vault particles remains largely elusive. (Figure 1A).
Here, we demonstrate for the first time that regulation of the whole vault complex, including intracellular upregulation of vault RNAs and their specific exosomal release into the TME, was directly correlated with therapeutic responsiveness in two models of endocrine tumors in vitro and in vivo (Figure 1B). Upon successful tumor tissue damage in all cases, components of the vault complex were increased and vault RNAs were specif- ically released, accompanying upregulation of certain autophagic markers that could be exclusively observed upon treatment with classical or liposomally encapsulated cytostatics. Conversely, a downregulation of autophagic markers was observed upon treatment with other drug classes directly related to immune system regulation.
A
cap domain
TEP1
vPARP
vPARP
shoulder domain
vPARP
vPARP
R9
R8
R7
barrel domain
R6
TEP1
R5
R4
R3
R2
R1
vtRNA1-1 vtRNA1-2 vtRNA1-3
B
up- or downregulation of autophagy (dependent on cell-damaging signal)
Exocytotic transport
tumor cell damage 3
Loading into exosomal vesicles
Nucleo-cytoplasmatic transport
Cytosol
Nucleus
2. Materials and Methods
2.1. Cell Culture, In Vivo Experiments and Gene Array
NCI-H295R and BON cell culture, in vivo experiments, and gene array were performed as previously described in detail [16,17]
2.2. Immunofluorescence/Histochemistry
BON and NCI-H295R cells were seeded on 4-well glass chamber slides (Sarstedt, Nümbrecht, Germany) and treated for 2 h with 0.1 µg/mL TNFx on the following day. Cells were fixed with 4% PFA solution (Sigma-Aldrich, St. Louis, MO, USA) and treated with citrate buffer for epitope retrieval. To locate MVP, the mouse anti-MVP antibody (Abcam, Cambridge, UK) and Alexa Fluor488-labeled donkey anti-mouse antibody (Thermo Fisher, Waltham, MA, USA) were used.
Sections (4 um) of BON and NCI-H295R FFPE tumors from ASA resp. NCI-H295R FFPE tumors in EDPM/LEDPM-treated mice were deparaffinized, rehydrated, and after HIER treatment in citrate buffer, peroxidase was blocked with 0.3% H2O2. Subsequently, sections were incubated with blocking buffer containing 3% BSA (Roche Diagnostics, Basel, Switzerland), 5% goat serum (Jackson ImmunoResearch Laboratories, West Grove, PA, USA), and 0.5% Tween 20 (Sigma-Aldrich), followed by incubation with rabbit monoclonal anti-LC3B antibody (Abcam) at +4 ℃ overnight. The secondary antibody used was biotiny- lated goat anti-rabbit antibody (Vector Laboratories, Newark, CA, USA). Sections were then processed with the Vectastain Elite ABC kit, visualized by DAB, and counterstained with Methyl Green (all three, Vector Laboratories).
2.3. EV Isolation by Ultracentrifugation
EVs were purified by differential centrifugation processes, as previously described [18]. Briefly, NCI-H295R and BON cells were seeded into 15 cm dishes in complete medium. After reaching 70-80% confluency, the cells were washed with PBS and subsequently incubated in exosome-depleted FBS for 48 h. The conditioned medium was first centrifuged at 600x g for 10 min to remove cells and then centrifuged at 2000x g for 15 min to remove debris. The resulting precleared supernatant was then ultracentrifuged in a 70Ti rotor (Beckman-Coulter, Brea, CA, USA) at 10,000x g for 30 min at 4 ℃ and then sequentially ultracentrifuged at 100,000x g for 70 min at 4 ℃. The supernatant was discarded and the pellet was washed in PBS using the same ultracentrifuge conditions. The pellet containing the purified EVs was collected in PBS buffer and passed through a 0.2 um pore filter.
2.4. EV Isolation by ExoQuick
The ExoQuick kit was used according to the manufacturer’s instructions (System Bio- sciences, Catalog no. EXOQ5A-1, Palo Alto, CA, USA). In brief, after reaching 70-80% confluency, the NCI-H295R and BON cells were washed with PBS and subsequently incu- bated in exosome-depleted FBS for 48 h. An initial spin was performed at 10,000x g (room temperature) for 10 min to remove cells and debris from each sample, then the corresponding amounts of reagents were added proportional to the starting sample volume, according to the manufacturer’s instructions. Mixtures were vortexed and incubated at 4 ℃ for up to an hour and then centrifuged at room temperature to precipitate the exosome pellets. Regarding the centrifugation parameters, it was performed for 30 min at 1500x g, followed by pellet resuspension in 100 uL PBS buffer. All exosomes were stored at -80 ℃ immediately after isolation until further NTA analysis.
2.5. Nanoparticle Tracking Analysis (NTA)
The size distribution and concentration of nanoparticles in 2D and 3D EV isolations were assessed using the NanoSight NS300 device (Malvern Panalytical, Malvern, UK). Samples were diluted 1:100 in order to obtain an optimal detectable concentration of 40-80 particles/frame.
sCMOS camera levels were kept at 14-15 depending on the concentration of samples. Samples were injected in the 488 nm laser chamber with a constant output controlled by a syringe pump. Five 60 s video recordings were performed for each sample. NTA software (NTA 3.1 Build 3.1.54, Malvern Panalytical, Malvern, UK) was used to analyze the data with a detection threshold of 3. GraphPad Prism (v8.4.2, GraphPad Software, San Diego, CA, USA) was used to integrate the five technical measurements of each sample.
2.6. Si-RNA Experiments
NCI-H295R and BON cells (5 million cells/well) were seeded in two 150 cm2 flasks per group in penicillin/streptomycin-free medium (day 0). For small interfering RNA (siRNA)-mediated knockdown of MVP, TEP1, and PARP4, cells were transfected with 100 nM of either the targeting or control (siRNA SMARTpool: ON-TARGETplus MVP siRNA L-004984-01-0020, siRNA SMARTpool: ON-TARGETplus TEP1 siRNA L-012377- 00-0005, siRNA SMARTpool: ON-TARGETplus PARP4 siRNA L-007244-00-0005, and ON-TARGETplus Non-targeting Pool D-001810-10-05; Dharmacon, Lafayette, CO, USA) using Lipofectamine RNAiMAX Reagent (#3778030, Invitrogen™M, Waltham, MA, USA) in Opti-MEM medium (#31985062 Gibco™M, Waltham, MA, USA). On day 2, the cells were induced with 0.1 µg/mL TNFx. On day 3 (48 h after transfection), the cells and culture media were harvested. RNA from the cells was extracted using the RNeasy Mini kit (Qiagen, Hilden, Germany), followed by DNA removal (TURBO DNA-free™M Kit, Thermo Fisher). For cDNA synthesis, 410 ng RNA and the RevertAid™M H Minus First Strand cDNA Synthesis Kit (Thermo Fisher) was used.
2.7. RNA Isolation, Reverse Transcription and qRT-PCR
RNA from ASA-treated and control tumors was extracted using the RNeasy Mini kit (Qiagen), followed by DNA removal (TURBO DNA-free™M Kit, Thermo Fisher). For cDNA synthesis, 1.5 µg RNA and the RevertAid™M H Minus First Strand cDNA Synthesis Kit (Thermo Fisher) was used.
For real-time PCR analysis of the ASA-treated BON and NCI-H295R tumors, Sso- Fast EvaGreen reaction mix (Bio-Rad Laboratories, Hercules, CA, USA) in the MX3000P cycler (Stratagene, La Jolla, CA, USA) was used. The following PCR primers were used: human vault RNA1-1 (forward: 5’-TAGCTCAGCGGTTACTTCGACAGTTCT, reverse: 5’- GGGTCTCGAACAACCCAGACAGG), human vault RNA1-2 (forward: 5’-CGAGTACATT GTAACCACCTCTCTGGG, reverse: 5’-AAGAGCTGGAAAGCACCCGC), and human vault RNA1-3 (forward: 5’-CTCAGCGGTTACTTCGCGTGTCA, reverse: 5’-CGCCCGCG GGTCTCGAACAA). For real-time PCR analysis of the transfected BON and NCI-H295R cells, SsoFast EvaGreen reaction mix (Bio-Rad Laboratories) in the AB7500fast cycler (Ap- plied Biosystems) was used. The following PCR primers were used: human MVP (for- ward: 5’-GGGTGAGAGTTCCCCATCTG, reverse: 5’-GGCTCACAAGAAGATGACTGGT), human TEP1 (Real Time Primers, Elkins Park, PA, USA; forward: 5’- CCCAAGTCC- CTGAACTGTGT, reverse: 5’-ACATTGAAGGCCAAGGTACG), and human PARP4 (Ori- gene, Rockville, DE, USA; forward: 5’-CATGGCGCTTACCTGATGAGTC, reverse: 5’- AACAGTGCCCAGGATGCTGAGT). All gene expression levels in the RNA originated from the cells were normalized to human GAPDH (forward: 5’-AGCCTCCCGCTTCGCTCTCT, reverse: 5’-CCAGGCGCCCAATACGACCA), whereas the exosomal gene expression lev- els were normalized to miR-15a (forward: Hs_miR-15a_1, Qiagen MS00003178, reverse: miScript Universal Primer, Qiagen).
For real-time PCR analysis of the cell culture supernatants, cells were seeded in 6-well plates and treated with 0.1 µg/mL TNFx on the following day. After 24 h, the supernatants were collected and cleared of cellular debris. Free-floating microRNA was extracted from the supernatant using the Nucleospin RNAII kit (Macherey-Nagel, Düren, Germany). A 12 uL aliquot of the RNA solution and the RevertAid™M H Minus First Strand cDNA Synthesis Kit (Thermo Fisher) and miScript kit (Qiagen) were used for cDNA synthesis. Real-time PCR for vault RNA1-1, vault RNA1-2, and vault RNA1-3 was performed using the SsoFast EvaGreen reaction mix (Bio-Rad Laboratories) in the MX3000P cycler (Stratagene). The miScript miR15a primer (Qiagen) was used for normalization.
2.8. Western Blot
2.8.1. BON, NCI ASA Tumors
One million BON and NCI-295R cells per well were seeded in 6-well plates and treated for 2 and 6 h, respectively, with TNFx on the following day. Cells were lysed in the RIPA buffer
containing Complete Mini Protease Inhibitor Cocktail (Roche, Basel, Switzerland). The protein concentration was measured using the BCA kit (Thermo Fisher) with the PowerWave340 plate reader (Biotek, Winooski, VT, USA). With 10 µg of proteins loaded per well on the 3.9-20% gel, PAGE was performed for 2 h 30 min at constant voltage of 30 mA per gel in Mini-PROTEAN Tetra Vertical Electrophoresis Cell (Bio-Rad, Hercules, CA, USA).
The eBlot transfer system (Genscript, Piscataway Township, NJ, USA) was used for protein transfer on NC membranes. After blocking with NET-G buffer for 1 h, the membranes were incubated with LC3B antibody (Abcam) at +4 ℃ overnight, washed, and incubated with the HRP-labeled anti-rabbit antibody (GE Healthcare, Chicago, IL, USA) for 1 h at RT. For visualization, Lumi-Light ECL (Roche) and the LAS3000 imager (Fujifilm, Minato, Tokyo, Japan) were used. Subsequently, membranes were washed, blocked with NET-G, and incubated with mouse ß-actin antibody (Sigma-Aldrich) at +4 ℃ overnight. As the secondary antibody, HRP-labeled anti-mouse antibody (GE Healthcare) was used. ß-actin was visualized with Lumi-Light ECL in LAS3000.
2.8.2. NCI EDPM Cells
One million NCI-H295R cells per well were seeded in a 6-well plate and treated with 0.25 x IC50 EDP-M for 24 h starting the following day. Cells were lysed in RIPA buffer containing Complete Mini Protease Inhibitor Cocktail (Roche). The protein concentration was measured using the BCA kit (Thermo Fisher) with the PowerWave340 plate reader. A sample with 20 µg of proteins was loaded on the 3.9-20% gel, which was then run for 4 h 15 min (first at constant voltage of 50 V for 45 min, and then at constant voltage of 200 V for 3 h 30 min) in the Mini-PROTEAN Tetra cell. Protein transfer, incubation with LC3B and ß-actin antibodies, visualization, and imaging were performed analogously to the protein samples from ASA-treated tumors. In this setting, for quantification of the LC3B band in Figure 6G the bands were straightened using ImageJ.
2.8.3. BON, NCI TNF Cells
A total of 0.7 m BON and 1 m NCI-295R cells per well were seeded in 6-well plates and treated for 24 h with 0.1 ug/mL TNF« starting the following day. Cells were lysed in RIPA buffer containing Complete Mini Protease Inhibitor Cocktail (Roche). The protein concentration was measured using the BCA kit (Thermo Fisher) with the Tecan Sunrise plate reader (Tecan, Männedorf, Switzerland). A sample with 15 µg of proteins was loaded on Any kDTM Mini-PROTEAN® TGX Stain-FreeTM Protein Gels (Bio-Rad, Hercules, CA, USA) and run at constant 100 V until the dye front reached the reference line of the gel. For protein transfer, PVDF membranes and Trans-Blot Semi-Dry Transfer Cell (Bio-Rad) were used. Membranes were cut and after blocking with Blotting-Grade Blocker (Bio-Rad), the upper halves were incubated with mouse anti-MVP antibody (Abcam, Cambridge, UK) and the lower halves were incubated with mouse ß-actin antibody (Sigma-Aldrich) at +4 ℃ overnight, washed, and incubated with HRP-labeled anti-mouse antibody (GE Healthcare). As the ECL substrate, Western Lightning Plus (PerkinElmer, Waltham, MA, USA) was used. The luminescence signal was captured with the Hyperfilm ECL (GE Healthcare).
2.9. Statistical Analysis
Statistical analysis and graphical representation of the data were carried out using Graph- Pad Prism software (version 8, GraphPad Software, La Jolla, CA, USA). If not stated otherwise, comparisons between the control group and two or more treatment groups or between cell lines (mean of each) were performed by one-way ANOVA followed by Bonferroni’s multiple comparisons test. The data are presented in column graphs depicting the mean ± SEM. Statistical significance is denoted as stars in the graphs (* p < 0.05; ** p < 0.01; *** p < 0.001).
3. Results
3.1. Investigation of Gene Transcripts Related to Therapeutic Responsiveness In Vivo
In a previous study, we investigated the therapeutic potential of the tumor vascular- disrupting agent ASA404 and its downstream mediator TNF« against endocrine tumors in xenograft models for neuroendocrine tumors of the gastroenteropancreatic system (BON) and adrenocortical carcinoma (NCI-H295R). While the BON tumor model demonstrated significant induction of TNF« upon ASA404 treatment and related high therapeutic respon- siveness in vivo, no comparable effects were detectable in the NCI-H295R xenografts [16].
The starting point of the current project was the in vivo investigation of specific intra- tumoral gene expression in the therapeutically responding vs. not responding model. Inter- estingly, a gene-array expression analysis of ASA404-treated BON and NCI tumors revealed that intra-tumoral vault RNA1-1 was almost 17-fold upregulated and thereby the most highly induced transcript upon ASA treatment in the responding BON tumor model (Table 1, [16]). In addition to vault RNA1-1, vault RNA1-2 (5-fold), and vault RNA1-3 (2.5-fold) were found to be significantly upregulated (Table 1). In the next step, we confirmed the specific upregulation of vault RNAs in therapeutically responding BON-tumors in independent real-time PCR analyses, as demonstrated in (Figure 2A-C).
| Entrez Gene ID | Abbreviation | RNA Type | BON | NCI | |
|---|---|---|---|---|---|
| 56664 | vault RNA1-1 | VTRNA1-1 | non-coding | 16.6 | 1.8 |
| 677823 | small nucleolar RNA, H/ACA box 42 | SNORA42 | non-coding | 10.1 | |
| 677775 | small Cajal body-specific RNA 5 | SCARNA5 | non-coding | 8.2 | |
| 677808 | small nucleolar RNA, H/ACA box 23 | SNORA23 | non-coding | 8.0 | 7.6 |
| 677774 | small Cajal body-specific RNA 1 | SCARNA1 | non-coding | 7.2 | 3.7 |
| 619565 | small nucleolar RNA, H/ACA box 52 | SNORA52 | non-coding | 6.6 | 3.1 |
| 677772 | small Cajal body-specific RNA 6 | SCARNA6 | non-coding | 6.4 | 2.6 |
| 677806 | small nucleolar RNA, H/ACA box 20 | SNORA20 | non-coding | 6.0 | 3.2 |
| 677819 | small nucleolar RNA, H/ACA box 37 | SNORA37 | non-coding | 5.7 | 2.6 |
| 677801 | small nucleolar RNA, H/ACA box 14A | SNORA14A | non-coding | 5.6 | 1.5 |
| 1349 | cytochrome c oxidase subunit VIIb | COX7B | coding | 5.4 | 1.8 |
| 56663 | vault RNA1-2 | VTRNA1-2 | non-coding | 5.0 | 2.3 |
| 26829 | RNA, U5E small nuclear 1 | RNU5E-1 | non-coding | 4.9 | 2.8 |
| 26784 | small nucleolar RNA, H/ACA box 64 | SNORA64 | non-coding | 4.4 | 2.8 |
| 677797 | small nucleolar RNA, H/ACA box 7B | SNORA7B | non-coding | 4.4 | 2.0 |
| 619505 | small nucleolar RNA, H/ACA box 21 | SNORA21 | non-coding | 4.2 | 1.9 |
| 6044 | small nucleolar RNA, H/ACA box 62 | SNORA62 | non-coding | 4.1 | |
| 677802 | small nucleolar RNA, H/ACA box 14B | SNORA14B | non-coding | 4.1 | |
| 692148 | small Cajal body-specific RNA 10 | SCARNA10 | non-coding | 4.1 | 2.7 |
| 677837 | small nucleolar RNA, H/ACA box 60 | SNORA60 | non-coding | 4.1 | 1.5 |
| 574040 | small nucleolar RNA, H/ACA box 6 | SNORA6 | non-coding | 4.1 | |
| 677811 | small nucleolar RNA, H/ACA box 28 | SNORA28 | non-coding | 4.0 | 2.2 |
| 6286 | S100 calcium binding protein P | S100P | coding | 3.9 | |
| 677825 | small nucleolar RNA, H/ACA box 44 | SNORA44 | non-coding | 3.9 | |
| 692158 | small nucleolar RNA, H/ACA box 57 | SNORA57 | non-coding | 3.8 | 2.0 |
| 677781 | small Cajal body-specific RNA 16 | SCARNA16 | non-coding | 3.8 | |
| 619568 | small nucleolar RNA, H/ACA box 4 | SNORA4 | non-coding | 3.6 | |
| 26824 | RNA, U11 small nuclear | RNU11 | non-coding | 3.6 | |
| Entrez Gene ID | Abbreviation | RNA Type | BON | NCI | |
|---|---|---|---|---|---|
| 677773 | small Cajal body-specific RNA 23 | SCARNA23 | non-coding | 3.5 | 1.8 |
| 85495 | ribonuclease P RNA component H1 | RPPH1 | non-coding | 3.4 | 1.7 |
| 26776 | small nucleolar RNA, H/ACA box 71B | SNORA71B | non-coding | 3.3 | |
| 541471 | uncharacterized LOC541471 | LOC541471 | coding | 3.3 | |
| 100033436 | small nucleolar RNA, C/D box 116-25 | SNORD116-25 | non-coding | 3.3 | 1.8 |
| 114599 | small nucleolar RNA, C/D box 15B | SNORD15B | non-coding | 3.2 | 1.9 |
| 677809 | small nucleolar RNA, H/ACA box 24 | SNORA24 | non-coding | 3.2 | 2.4 |
| 401466 | chromosome 8 open reading frame 59 | C8orf59 | coding | 3.0 | |
| 100151683 | RNA, U4atac small nuclear (U12-dependent splicing) | RNU4ATAC | non-coding | 3.0 | 1.6 |
| 692225 | small nucleolar RNA, C/D box 94 | SNORD94 | non-coding | 3.0 | |
| 100033438 | small nucleolar RNA, C/D box 116-26 | SNORD116-26 | non-coding | 3.0 | 2.4 |
| 4477 | microseminoprotein, beta- | MSMB | coding | 2.9 | |
| 677829 | small nucleolar RNA, H/ACA box 49 | SNORA49 | non-coding | 2.9 | 1.8 |
| 9446 | glutathione S-transferase omega 1 | GSTO1 | coding | 2.9 | |
| 93081 | testis expressed 30 | TEX30 | coding | 2.9 | |
| 51642 | mitochondrial ribosomal protein L48 | MRPL48 | coding | 2.8 | 1.9 |
| 5203 | prefoldin subunit 4 | PFDN4 | coding | 2.8 | |
| 677793 | small nucleolar RNA, H/ ACA box 2A | SNORA2A | non-coding | 2.8 | |
| 521 | ATP synthase, H+ transporting, mitochondrial Fo complex, subunit E | ATP5I | coding | 2.8 | |
| 3957 | lectin, galactoside-binding, soluble, 2 | LGALS2 | coding | 2.8 | |
| 4709 | NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 3, 12kDa | NDUFB3 | coding | 2.8 | 1.6 |
| 51503 | CWC15 spliceosome-associated protein homolog (S. cerevisiae) | CWC15 | coding | 2.7 | 1.7 |
| 6750 | somatostatin | SST | coding | 2.7 | |
| 594839 | small nucleolar RNA, H/ACA box 33 | SNORA33 | non-coding | 2.7 | |
| 25826 | small nucleolar RNA, C/D box 82 | SNORD82 | non-coding | 2.7 | 1.6 |
| 6201 | ribosomal protein S7 | RPS7 | coding | 2.7 | 1.9 |
| 677770 | small Cajal body-specific RNA 22 | SCARNA22 | non-coding | 2.7 | 2.2 |
| 677798 | small nucleolar RNA, H/ ACA box 9 | SNORA9 | non-coding | 2.7 | |
| 26777 | small nucleolar RNA, H/ACA box 71A | SNORA71A | non-coding | 2.7 | 1.5 |
| 7012 | telomerase RNA component | TERC | non-coding | 2.7 | |
| 677777 | small Cajal body-specific RNA 12 | SCARNA12 | non-coding | 2.7 | 1.6 |
| 10247 | heat-responsive protein 12 | HRSP12 | coding | 2.6 | |
| 100033431 | small nucleolar RNA, C/D box 116-20 | SNORD116-20 | non-coding | 2.6 | 1.6 |
| 84300 | mitochondrial nucleoid factor 1 | MNF1 | coding | 2.6 | 1.6 |
| 3434 | interferon-induced protein with tetratricopeptide repeats 1 | IFIT1 | coding | 2.6 | 2.8 |
| 319103 | small nucleolar RNA, C/D box 8 | SNORD8 | non-coding | 2.6 | |
| 677814 | small nucleolar RNA, H/ACA box 31 | SNORA31 | non-coding | 2.6 | |
| 100033821 | small nucleolar RNA, C/D box 116-29 | SNORD116-29 | non-coding | 2.6 | 1.6 |
| 4338 | molybdenum cofactor synthesis 2 | MOCS2 | coding | 2.6 | 2.4 |
| 29950 | SERTA domain containing 1 | SERTAD1 | coding | 2.6 | 2.1 |
| 25906 | anaphase promoting complex subunit 15 | ANAPC15 | coding | 2.6 | 2.0 |
| 26828 | RNA, U5F small nuclear 1 | RNU5F-1 | non-coding | 2.6 | |
| 116937 | small nucleolar RNA, C/D box 83A | SNORD83A | non-coding | 2.6 | |
| 6206 | ribosomal protein S12 | RPS12 | coding | 2.6 | |
| 51053 | geminin, DNA replication inhibitor | GMNN | coding | 2.6 | |
| 100033420 | small nucleolar RNA, C/D box 116-8 | SNORD116-8 | non-coding | 2.6 | 2.2 |
| Entrez Gene ID | Abbreviation | RNA Type | BON | NCI | |
|---|---|---|---|---|---|
| 57819 | LSM2 homolog, U6 small nuclear RNA associated (S. cerevisiae) | LSM2 | non-coding | 2.6 | 1.8 |
| 677833 | small nucleolar RNA, H/ACA box 54 | SNORA54 | non-coding | 2.6 | |
| 56662 | vault RNA1-3 | VTRNA1-3 | non-coding | 2.5 | |
| 119392 | SWI5-dependent recombination repair 1 | SFR1 | coding | 2.5 | 1.6 |
| 341 | apolipoprotein C-I | APOC1 | coding | 2.5 | |
| 30836 | deoxynucleotidyltransferase, terminal, interacting protein 2 | DNTTIP2 | coding | 2.5 | 1.8 |
| 8365 | histone cluster 1, H4h | HIST1H4H | coding | 2.5 | |
| 6643 | sorting nexin 2 | SNX2 | coding | 2.5 | 2.7 |
| 200916 | ribosomal protein L22-like 1 | RPL22L1 | coding | 2.5 | |
| 26804 | small nucleolar RNA, C/D box 45B | SNORD45B | non-coding | 2.5 | 2.7 |
| 1347 | cytochrome c oxidase subunit VIIa polypeptide 2 (liver) | COX7A2 | coding | 2.5 | 1.5 |
| 174 | alpha-fetoprotein | AFP | coding | 2.5 |
A
3000
B
3000
C
1250-
vaultRNA 1-1 [% of control]
1000
2000
vaultRNA 1-2 [% of control]
2000
vaultRNA 1-3 [% of control]
750
1000
1000
500
250
0
0
0
NCI ø
NCI ASA
BON ø
BON ASA
NCI ø
NCI ASA
BON ø
BON ASA
NCI ø
NC ASA
BON ø
BON ASA
D
200-
MVP - Western Blot [% of control]
E
175
NCI
NCI + TNFa
BON
BON + TNFa
150
MVP
125-
100
Beta actin- -
75
NCI ø
NCI TNFa
BON ø
BON TNFa
G
MVP Knockdown
F
MVP / GAPDH gene expression
5
R
5
a.
UT
si-NT
si-MVP
UT
si-NT
si-MVP
UT
si-NT
si-MVP
UT
si-NIT
si-MVP
no TNF-a
with TNF-a.
no TNF-a
with TNF-a
BON untreated
BON + TNFa
.
BON
NCI-H295R
H
BON
TEP1 Knockdown
Viable Cell Number
ns
TEP1 / GAPDH
gene expresison
1.5+
-
4× 10*
.
-
…
15
a
,
0
UT
si-NT
si-MVP
si-TEP1
si-PARP4
UT
si-NT
si-MVP
si-TEP1
si-PARP4
UT
si-NT
si-TEP1
UT
si-NT
si-TEP1
UT
si-NT
si-TEP1
பா
si-NT
si-TEP1
no TNF-a
with TNF-a
no TNF-&
with TNF-a
No TNF-a
With TNF-a
BON
NCI-H295R
C
NCI-H295R
K
éxta*
PARP4 Knockdown
Viable Cell Number
ns
2.0-
PARP4 / GAPDH
gene expression
1.5
.0
1
15
O
UT
SI-NT
si-MVP
Si-TEP1
si-PARP4-
UT-
SI-NT
si-MVP
si-TEP1
si-PARP4-
A
UT
si-NIT
si-PARP4
UT
si-NT si-PARP4
UT
Sİ-NT
I-PARP4
UT
SÅ-NT
si-PARP4
no TNF-a
with TNF-a
no TNF-a
with TNF-a
No TNF-@
With TNF-@
BON
NCI-H295R
M
N
400
300
200-
vaultRNA 1-1
in culture medium [% of control]
vaultRNA 1-2
In culture medium [% of control]
vaultRNA 1-3
in culture medium [% of control]
300
200
200
100
100
100
0
0
0
NCI ø
NCI TNFa
BON @
BON TNFa
NCI ø
NCI
TNFa
BON ø
BON
INFa
NCI ø
NCI
INFa
BON @
BON TNFa
stimulated BON and NCI-H295R tumor cells. MVP, TEP-1, and PARP4 gene expression analysis (G,I,K) and cell viabilities (H,J) under TNF« stimulation and specific si-RNA knockdown. Vault RNA levels in cell culture supernatants of TNFx-stimulated BON and NCI-H295R tumor cells (L-N). The statistical significance is denoted as stars or as rhomb (vs. UT no TNF«) in the graphs (*p<0.05; ** p < 0.01; *** p < 0.001), : statistical significance UT no TNF alpha vs. UT with TNF alpha p < 0.001. The whole western blots are show in File S1.
3.2. Investigation of the Vault Complex in Therapeutically Responding vs. Not-Responding Tumors
To investigate whether the observed regulation was also accompanied by the regula- tion of other components of the vault complex, we made for further investigations usage of the in this context established therapeutic mediator TNF& as ASA404s initial therapeutic mechanism of vascular disruption cannot be represented in in vitro settings. These ex- periments revealed that, under these conditions, there was also a significant increase in MVP and TEP-1 but not in PARP4 (VPARP) gene expression upon TNFx treatment in the therapeutically responding model only (Figure 2G-K, blue columns indicate therapeutically responsive BON cells and green columns indicate therapeutically not-responding NCI- H295R cells). Moreover, these effects could be correlated with a significant increase in MVP protein, as demonstrated by immunofluorescence (Figure 2F) and quantified by western blot analysis (Figure 2D,E). To investigate whether a specific reduction in MVP, TEP-1, or PARP4 led to cytotoxic or cytoprotective effects, we also performed si-RNA knockdown experiments, which indicated overall that modulation of these components of the vault complex (Figure 2G-K) might have a general influence on cell viability in both tumor models (Figure 2H,J). Subsequent experiments revealed that TNF« treatment also resulted in a highly significant accumulation of vault RNA1-1 in the cell culture supernatants of BON cells, while no such effect was detectable for therapeutically unresponsive NCI-H295R cells under these conditions (Figure 2L-N).
3.3. Investigation of Exosomal Release of TNFa-Treated BON and NCI-H295R Cells
To follow up on the observed specific vault RNA1-1 accumulation in the cell culture supernatants, we next isolated the exosomes from these cell culture supernatants and performed nanoparticle tracking analysis (NTA). NTA allows the investigation of size dis- tribution and relative concentration of extracellular vesicles/mL in cell culture supernatant or bodily fluid. As the methodological gold standard for the isolation of exosomes remains under debate, we further included two standards in our exosome-related experiments in all settings: (a) a kit purification (ExoQuick) and (b) ultracentrifugation. As presented in Figure 3, these experiments revealed successful isolation of extracellular vesicles by both methods, leading to preparations that demonstrated specific peaks in the expected exosomal size range in the subsequent NTA analysis. For the quantification of particle concentration/mL, we included four exemplary pictures representing secreted vesicle quantities. However, it has to be mentioned that no clear correlation between therapeutic responsiveness and quantities of released exosomes was detected overall. In contrast, we found a clear correlation with the loading of vault RNA1-1 content into these exosomes. As depicted in Figure 4, our experiments not only revealed a highly significant increase in intracellularly increased vault RNA1-1 expression, but we also found significantly elevated levels of exosomally released vault RNA1-1 from TNFx-treated BON cells.
A
NCI-H295R
B
Concentration (particle / ml)
Concentration (particle / ml)
Concentration (particle / ml)
Exoquick
54
48
40-
Concentration (particle/ml)
8x101
20
10
10-
6×1010,
8
-
«
200
300
500
2
Size (nm)
200
000
900
8000
0
Size (nm)
Do
-
-
3
2
-
Size (nm)
-
-
®
4×1010,
Concentration (particle / ml)
1a
Concentration (particle / ml)
Concentration (particle / ml)
15-
L
+ TNF
·
+ TNF
1ª
+ TNF
2×1010,
ON
9
15
.
0
”
..
15
Control
TNF-a.
6
10
63
À
10
1
1
01
0
16
1
Size (nm)
-
0
-
6
-
Size (nm)
to
100
-
00
2010
200
500
Size (nm)
NO
1
CIE
C
BON
D
Concentration (particle / ml)
6ª
Concentration (particle / ml)
Concentration (particle / ml)
5.0
Concentration (particle/ml)
&#
5x101
19
3
KO
4×1010,
*
SU
0
T
2ª
20-
40
3×10 10
19
Q
10
2×1010-
0
0
#
1
#
200
-
Size (nm)
-
200
1000
.
200
300
Size (nm)
500
600
000
900
6
-
400
Size (nm)
8CHO
1x10 10,
Concentration (particle / ml)
5.0
Concentration (particle / ml)
18
Concentration (particle / ml)
3.00
..
0
T
T
+ TNF
0
+ TNF
+ TNF
Control
TNF-a
10
.
30
20
0
10
18
a
M
0
2
100
200
300
500
e
Size (nm)
800
3
-
-
-
-
3
Size (nm)
1000
0
100
-
30
Size (nm)
400
-
-
-
E
NCI-H295R
F
Concentration (particle / ml)
5B - 1
Concentration (particle / ml)
Ultracentrifugation
45 -
Concentration (particle / ml)
40-
25 -
Concentration (particle/ml)
6×1010,
**
6 .
T
4×1010,
0
IM
U
-
500
Size (nm)
-
500
680
790
800
0
200
300
40%
800
500
000
-
Size (nm)
600
0
Size (nm)
-
Concentration (particle / ml)
25
Concentration (particle / ml)
15
Concentration (particle / ml)
10
IF
2×1010,
-
38
12
3.6
15-
+ TNF
+ TNF
25
+ TNF
3%
25
0
Y
18-
3.
Control
TNF-a
15
15
1.0
af
P
20
2
a
200
300
500
600
-
·
Size (nm)
300
Size (nm)
500
800
200
1000
-
200
Size (nm)
700
900
1000
G
BON
-
H
5.0
60
I
oncentration (particle / ml)
centration (particle / ml)
sa-
ncentration (particle / ml)
5.0-
40
40
10
Concentration (particle/ml)
30
30
3.0
4×1010
20 -
3×1010,
*
10
NO
T
0
3
M
1000
São
700
000
0
100
200
300
500
000
500
0
7
Size (nm)
Size (nm)
3
2×1010,
Concentration (particle / ml)
Concentration (particle / ml)
Concentration (particle / ml)
Size (nm)
S
**
1×1010,
40
.
+ TNF
+ TNF
15-
+ TNF
0
Control
TNF-a
20
=
10
LA
0
NO
200
1
1
100
=
0
1
Size (nm)
Size (nm)
-
.
200
300
-
Size (nm)
500
800
900
1800
A
Exoquick
Intracellular Vault RNA1-1 (Normalized to GAPDH)
Exosomal Vault RNA1-1 (Normalized to miR-15a)
BON
VaultRNA1-1 / GAPDH
gene expresison
Exosomal VaultRNA1-1 / miR15a
BON
250-
**
300
200-
gene expresison
200
150
100
100
50
0
0
Control
TNF-a
Control
TNF-a
NCI-H295R
NCI-H295R
250-
300-
VaultRNA1-1 / GAPDH
Exosomal VaultRNA1-1 / miR15a
200
gene expresison
gene expresison
200
150
100
100
50
0
0
Control
TNF-a
Control
TNF-a
B Ultracentrifugation
Intracellular Vault RNA1-1 (Normalized to GAPDH)
Exosomal Vault RNA1-1 (Normalized to miR-15a)
BON
VaultRNA1-1 / GAPDH
gene expresison
Exosomal VaultRNA1-1 / miR15a
BON
300
300-
200
gene expresison
200-
100
100
0
0
Control
TNF-a
Control
TNF-a
NCI-H295R
NCI-H295R
300-
300-
VaultRNA1-1 / GAPDH
gene expresison
Exosomal VaultRNA1-1 / miR15a
200
gene expresison
200
T
100
100
0
0
Control
TNF-a
Control
TNF-a
3.4. Correlation with Autophagic and Lysosomal Markers
For correlation with autophagic flux, we first investigated general LC3B abundance and potential occurrence of LC3BII puncta in ASA404-treated BON and NCI-H295R tumors. As depicted in Figure 5, the staining revealed overall for ASA404 treated BON-tumors that some treatment affected tumor regions (Figure 5A), which stained higher for LC3B (Figure 5C) com- pared to the NaCl-treated controls (Figure 5E), and also in NCI-H295R tumors (Figure 5B,D,F), but did not lead to obviously detectable LC3BII punctae under the chosen analytical setting. To further clarify this point in a more quantifiable setting, we complemented the in vitro setting again using TNF as an important therapeutic mediator of ASA404’s effects. While quantification of LC3B 2 h after TNFx treatment indicated some tendencies (not significant) towards increased protein levels, these tendencies were diminished after 6 h (Figure 5G). Fur- thermore, no significant changes in autophagic flux were reflected by the detected overall low levels of LC3BII in BON cells. This absence of potential modulation was comparable to that observed in NCI-H295R cells (Supplemental Figure S1). Moreover, the immunofluorescence
images confirmed these outcomes microscopically (Figure 5H). Of note, further investigations of human ATG5 and human LAMP1 (hLAMP1) demonstrated a significant downregulation of these markers in ASA-treated BON tumors. Murine LAMP1 (mLAMP1)-representing the lysosomal status of potentially infiltrated host macrophages into the tumor tissue-remained unchanged (Figure 5I).
BON NaCl
no ab
BON ASA
no ab
NCI NaCI
no ab
NCI ASA
no ab
A
B
100 g
7
100 g
100
2
6
10
100 g
100 gam
9
11
100 g
100 pm
100 gkm
12
3
100 jam
100 gmm
100 gam
100 gam
BON NaCl
NCI NaCI
C
D
1
2
3
No Antibody
7
8
9
No Antibody
BON ASA
NCI ASA
E
4
F
20 um
4
5
6
No Antibody
10
11
12
No Antibody
G
200
H
200
ATG5
mLAMP1
hLAMP1
BON LC3B / b-actin (% of ctrl)
Control
no ab ctr
TNF treatment
no ab cfr
150
BON DAR LCIS
gene expression / GAPDH (% of control)
150
100
3
100
**
50
NCI DAPI LCIO
50
0
2h
TNFa 2h
0
6h
TNFa 6h
+
ASA
+ ASA
+ ASA
3.5. Proof of Principle in NCI-H295R Tumors and Correlation with Autophagic and Lysosomal Markers upon Chemotherapeutic Treatment
Next, we hypothesized that if treatment-dependent modulation of the vault complex and exosomal release of vault RNAs are general mechanisms of action in affected endocrine tumor tissues, investigations of NCI-H295R tumors under a therapeutic scheme leading to approved tissue damage should reveal further insight.
The investigation of EDPM (etoposide, doxorubicin, cisplatin, mitotane)- and LEDPM (etoposide, liposomal doxorubicin, liposomal cisplatin, and mitotane)-treated NCI-H295R tumors had previously demonstrated significant anti-tumoral effects, including histologi- cally proven damage upon both treatment schemes [17,19]. Of note, as demonstrated in Figure 6, real-time PCR analysis under these conditions revealed for the first time a highly significant and treatment-dependent upregulation of vault RNAs also in NCI-H29R tumors
(Figure 6I,J). Subsequent immunohistochemical analysis of LC3B again demonstrated some affected areas (Figure 6E,F), which correlated with slightly higher staining intensity com- pared to control tumors (Figure 6D). However, under the defined microscopic conditions, the obtained images for NCI-H295 tumors did not really cluster in two clearly distinct groups (Figure 6A-C). Thus, for further clarification and optimized quantification, we performed western blotting and real-time PCR analysis again in parallel. In contrast to the previously analysed TNFx-treated tumors, these experiments demonstrated a clear upregulation of autophagic flux. Western blot analysis revealed a significant upregulation of LC3BI in EDPM-treated NCI-H295R cells, which was accompanied by the same tendency for LC3BII (Figure 6G). Following the same line, real-time PCR analysis of EDPM- and LEDPM-treated NCI-H295R tumors showed highly significant upregulation of ATG5 and hLAMP1 (Figure 6H).
LC3BI
LC3BII
Beta actin
Control
EDPM
LEDP
A
B
C
G
800
*
Control
EDPM
L
-
=
=
-
-
-
LC3B / b-actin (% of ctrl)
600
400
-
=
-
21
G
i
-
A
5
200
=
-
=
=
1
0
s
T
=
-
A
=
-
LC3BI control
LC3BI EDPM
LC3BII control
LC3BII EDPM
6
-
=
=
H
=
=
500
gene expression / GAPDH
ATG5
mLAMP1
hLAMP1
D
Control
R
%
-
-
**
1
2
3
(from2)
250
E
*
EDPM
T
M
4
-
5
6
(from6)
-
0
T
T
T
F
LEDP
control
EDPM
LEDPM
control
EDPM
LEDPM
control
EDPM
LEDPM
- 7
8
-
9
(from3)
=
Days
Day
1-3
Day 5
Day 6
Day 7
4
EDP-M
Mitotane
Doxorubicin
Etoposide
Etoposide + Cisplatin
Etoposide + Cisplatin
400-
200-
300
*
vRNA 1-1 / GAPDH [% of control]
300
VRNA 1-2 / GAPDH [% of control]
175
VRNA 1-3 / GAPDH [% of control]
150
200
200
125
100
100-
100
0
NaCl
EDPM
75
NaCl
EDPM
0
NaCl
EDPM
Days 1-3
Day
Day
Day 6
Day 7
4
5
J
Etoposide
Etoposide +
LEDP-M
Mitotane
Liposomal DXR
Etoposide
Liposomal Cisplatin
Liposomal Cisplatin
300-
200-
*
140-
vaultRNA 1-1 [% of control]
200
vaultRNA 1-2 [% of control]
150
vaultRNA 1-3 [% of control]
130
120
100-
100-
110
100
0
NaCl
LEDPM
50
90
NaCl
LEDPM
NaCl
LEDPM
,
blot in vitro (G). ATG5, murine LAMP-1, and human LAMP-1 gene expression analysis in NaCl-, EDPM-, and LEDPM-treated NCI-H295 tumors in vivo (H). The statistical significance is based upon one-way ANOVA, including Dunnett-s post-test vs. controls and is denoted as stars (* p < 0.05; ** p < 0.01; *** p < 0.001). Vault RNA1-1, 1-2, and 1-3 real-time PCR analysis of EDPM- (I) and LEDPM- (J) treated NCI-H295R tumors (two-tailed unpaired t-test).
4. Discussion
Vault particles, with sizes of 13 MDa, are the largest ribonucleoproteins identified to date, and their high copy numbers (10,000-100,000 per cell) and highly conserved composi- tions suggest fundamental functions in eukaryotic cells [10]. Interestingly, more than 95% of vault RNAs have been shown to be not directly associated with the protein complex [13]. This finding led in past years to the hypothesis that separate or additional functions might exist for vault RNAs. Indeed, most recently, it was demonstrated that vault RNA1-1 binds to the autophagic p62 receptor, which carries a specific LC3-interaction motif and co-localizes with LC3-positive autophagosomes [8,20,21]. Vault RNA1-1 has been shown to inhibit its function in autophagy under conditions of cellular stress and starvation [8,10]. A reduction of vault RNA1-1 levels during starvation is associated with decreased binding to p62 and subsequent promotion of p62 oligomerization and autophagy. So far, it has remained widely unclear to which extent vault RNA regulation and the subsequent modulation of autophagy are involved in further pathological settings such as cancer [8]. However, most recently, it was demonstrated that vault RNA1-1 knockout in human hepatocellular carcinoma cells led to defects in lysosome function, impairment of autophagy-mediated clearance, and subsequently potentiated effects of the multikinase inhibitor sorafenib [7]. Of note, a strong and specific upregulation of vault RNAs, as detected in our experiments upon tumor damage, has been previously described upon different viral infections [22,23]. Interestingly, as a trigger for the specific upregulation under these conditions, the latent membrane protein 1 (LMP1) was identified. LMP1 is a viral relative of the TNF receptor family, which mimics and shares important parts of IL-1 and TNFx-pathways [24,25]. Fit- tingly, in our study, TNFx was a strong stimulator of vault RNA, MVP, and TEP1 gene expression and also MVP protein expression in the TNFa-responsive BON tumor model. Moreover, upon TNF« treatment, we detected specific exosomal release of vault RNA1- 1. Interestingly, it was previously demonstrated that mouse colon cancer cells secrete exosomes containing MVP and that knockout of MVP led to miR-193a accumulation in donor cells instead of exosomes [26]. Our own preliminary data indicated that knockdown of MVP, TEP1, and PARP4 under TNFx-stimulated conditions might also block loading of vault RNA1-1 into exosomes (Supplemental Figure S2). Unfortunately, our initially implemented non-target control in two independent experiments also led to a significant downregulation of vault RNA1-1 loading specifically under TNFx stimulation in the BON tumor model. Therefore, this unspecific effect needs to be further clarified. However, it is well known that the process of recognition and response to non-self nucleic acids, such as siRNA, is governed by the innate immune system leading to induction of interferon and cytokine synthesis [27]. Thus, there is a clear rationale that simultaneous internal and external stimulation of small nucleic acids, including subsequent communications with the innate immune system, might interact here in some way. However, such potentially complex interactions need to be clarified in more detail in further experiments and were out of the scope of the current project.
In the past years, immunotherapy has gained more and more attention, including new immunotherapeutic approaches against cancer. However, side effects are regularly observed, which hampers the successful completion of clinical trials and their approval for clinical use [27]. Immunostimulatory nucleic acids, which are used in immunother- apy, are known to induce the innate immune system, including cytokine and interferon system activation. Moreover, naturally occurring exogenous nucleic acids are also usually involved in pathogen invasion and initiate in a comparable manner to the innate immune response. It is furthermore known that cells signal both via so called pathogen-associated
molecular pattern (PAMP) and damage-associated molecular pattern (DAMP) recognition pathways, and as outlined before under both conditions (TNFx- and LMP1-controlled [22]), a significant increase in vault RNAs was detected by us and others. Our experiments further revealed a specific exosomal release of vault RNAs upon tumor cell damage (TNFx- dependent or independent). Thus, it is prudent to speculate that the appropriate release of vault RNA-loaded exosomal vesicles might also have an influence on therapeutic outcomes via interaction with neighboring tumor cells but also with cells of the immune system.
The location of DAMP and PAMP receptors in endosomes and lysosomes, together with the previously described riboregulation of autophagy by vault RNA1-1, indicates roles in clearance and recycling via pathways that modify autophagic flux [8,27,28]. However, while the induction of components of the vault complex was clearly associated with tissue damage in our study, we detected converse regulation of autophagy under different therapeutic settings. While we observed a downregulation of autophagy upon vascular disruption and subsequent local inflammation in BON cells, an upregulation of LC3B, ATG5, and LAMP1 was detected under multi-chemotherapeutic conditions in the NCI-H295R tumor model. Autophagy is known to be divergent and dependent on cancer context, such as tumor stage and therapy, thereby also hindering common clinical applicability of autophagy activators or inhibitors [29]. Our experiments indicated the same conflicting potential for the role of vault RNA1-1 as a riboregulator of autophagy in endocrine cancers, and thus requires further analysis. While a strength of the study was the inclusion of in vitro and in vivo data for two independent tumor entities, a limitation was that only one cell line was implemented for each tumor entity. Further studies including more representative cell lines reflecting broader heterogeneity will be required. Moreover, it is important to note that the scientific focus of this first study was not to show that the observed changes and modulation of the vault complex are the direct intracellular cause for the different therapeutic responsiveness. Instead, we aimed to show that the highly specific occurrence, exosomal release, and potentially also the loading can be rather correlated as kind of result in therapeutically responsive tumors of both types (BON, NCI-H295R). Interestingly, this was dependent on the highly specific therapeutic responsiveness of the tumor types observed upon different therapeutic regimens tested in vitro and in vivo (TNF&, ASA, or EDPM). Accordingly, our study clearly identifies vault RNA1-1 as a highly interesting therapeutic biomarker for endocrine tumors independent of tumor type and therapy but dependent on specific responsiveness, which could be, due to the detected exosomal release of vault RNAs, furthermore isolated from patients’ bodily fluids. Moreover, we aim to investigate the interplay with cells of the immune system in further studies, investigating them as potential recipients of these highly specifically released vault RNA-loaded exosomes. In sum, our findings reveal new insight into a potential implication of the vault complex in the therapeutic responsiveness of endocrine tumors.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/cancers15061783/s1, Figure S1: MVP and Beta-actin Western Blots of control and TNF alpha treated BON and NCI-H295R cells. LC3B und Beta-actin Western Blots of BON and NCI-H295R control (BC, NC) or TNF alpha (BT, NT) treated cells. LC3B und Beta-actin Western Blots of control and EDPM treated NCI-H295R cells; Figure S2: Differential loading of vault RNA 1 under various si-RNA knockdown conditions for control and TNF alpha treated BON and NCI-H295R cells.
Author Contributions: Conceptualization, C.H .; Data curation, I.S. and A.S .; Formal analysis, I.S., A.S. and C.H .; Funding acquisition, C.H .; Investigation, I.S., A.S. and C.H .; Methodology, I.S., A.M., E.L., A.S. and C.H .; Resources, S.B., S.N., F.B. and C.H .; Supervision, C.H .; Validation, A.S. and C.H .; Visualization, K.Z. and C.H .; Writing-original draft, I.S., A.S. and C.H .; Writing-review & editing, S.B., A.M., K.Z., S.N. and C.H. All authors have read and agreed to the published version of the manuscript.
Funding: This work received funding from the Deutsche Forschungsgemeinschaft (DFG; project no. HA 8297/1-1 to C.H. and project no. 314061271, TRR 205/1 to S.B., F.B., S.N., and C.H). Moreover, the project was supported by Immuno-TargET under the umbrella of University Medicine Zurich to C.H., F.B., and S.N.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: All data that were needed to evaluate the conclusions in the paper are present in the paper.
Acknowledgments: We would like to thank Norbert Polacek. He lent us an ear and gave us highly appreciated feedback. Many thanks for your support!
Conflicts of Interest: The authors have no conflict of interest to declare.
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