Suppression of SIGMAR1 hinders oral cancer cell growth via modulation of mitochondrial Ca2+ dynamics

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Unfortunately, OC is often associated with a high mortality rate and limited treatment options for patients. Herein, we used in silico analysis and in vitro assays to investigate the impact of the Sigma-1 receptor (SIGMAR1) in OC progression by evaluating mitochondrial function, calcium signaling and clonogenic growth. First, the data from the TCGA pan-cancer analysis revealed that SIGMAR1 was overexpressed in OC versus healthy tissue and related to a worse survival rate. Furthermore, we also demonstrated that SIGMAR1 silencing increased mitochondrial membrane potential, inhibited Ca 2+ influx and significantly decreased clonogenic growth of OC cells. Based on these findings, we suggest that SIGMAR1 may influence mitochondrial membrane potential and energy production by modulating Ca 2+ uptake, which is critically important to cellular survival. In addition, SIGMAR1 knockdown may offer a potential strategy to be further explored as treatment for OC. Oral cancer SIGMAR1 mitochondrial Ca2+ signaling therapeutic strategy Figures Figure 1 Figure 2 1 Introduction Globally, approximately 390,000 new cases of Oral Cancer (OC) are diagnosed annually, contributing to a significant health burden[ 1 ]. Of note, the OC primarily originates from the squamous cells lining the oral cavity, including the lips, tongue, gums, floor of the mouth, palate, and oropharynx [ 2 , 3 ]. Beyond that, the major risk factors of OC include use of tobacco, heavy alcohol consumption, betel nut chewing and HPV infection [ 4 ]. However, the diagnosis of OC typically involves a physical exam, biopsy, and imaging tests and, the treatment depends on the tumor's stage and location and may include surgery, radiation, chemotherapy, or adjuvant therapy. On the other hand, the prognosis varies based on the stage at diagnosis[ 5 ]. Despite this, the 5-year overall survival (OS) rate is below 65%, with high recurrence and metastasis rates [ 3 ]. Thus, the conventional treatments for OC face challenges such as tumor heterogeneity, treatment resistance, and adverse side effects, limiting their effectiveness in reducing tumor growth. In this conecction, the discovery of new biomarkers for OC therapy is crucial to advancing treatment options and improving patient outcomes. Emerging research identifies the Sigma-1 receptor (SIGMAR1) as a key factor in cancer biology, with roles in cellular pathophysiology, survival, and signaling, making it a promising target for cancer therapy [ 6 ]. Significantly, SIGMAR1 is a protein located in the endoplasmic reticulum (ER), where it regulates various cellular processes, including mitochondrial functions and calcium signaling [ 7 ]. This is highly relevant as it suggests that mitochondrial dysfunction contributes to the upregulation of calcium signaling, a key driver of cancer cell growth, progression, and various aspects of tumor development, including cellular metabolism and signaling [ 8 , 9 ]. Conversely, abnormalities in this delicate balance can impact cancer cell survival and tumor progression [ 10 , 11 ]. However, it remains unclear whether the SIGMAR1 receptor influences the regulation of mitochondrial function and calcium signaling in OC and whether it affects cancer cell survival. This study aimed to evaluate the effects of SIGMAR1 knockdown in OC cells, focusing on mitochondrial function, calcium homeostasis, and clonogenic growth. Our initial findings revealed that SIGMAR1 is significantly overexpressed in OC compared to normal tissue, and this upregulation correlates with poorer disease prognosis. Of note, SIGMAR1 silencing increased mitochondrial membrane potential and reduced cytosolic calcium influx, leading to a marked decrease in colony formation by the cells. Overall,for the first time, we suggest that SIGMAR1 may influence mitochondrial membrane potential and energy production by modulating Ca²⁺ uptake, making it critical for cellular survival. 2 Methodology 2.1 Integrative Pan-Cancer Analysis We used the Tumor Immune Estimation Resource (TIMER) ( https://cistrome.shinyapps.io/timer/ ) [ 12 ] to identify the differential expression levels of SIGMAR1 (tumor vs. matched normal tissues) in 23 different malignant tumors from the TCGA project. 2.2 Evaluation of the survival analysis The prognostic significance of the SIGMAR1 in OC samples was evaluated using the Kaplan–Meier Plotter tool available on R2: Genomics Analysis and Visualization Platform ( http://r2.amc.nl ), database (accessed on 09/15/2024). The p-value < 0.05 indicates statistical significance. 2.3 Network construction: Protein-Protein Interaction of SIGMAR1 The STRING tool, v.11.0, ( https://string-db.org/ ) [ 13 ], was used to create a Homo Sapiens SIGMAR1 co-expression network. Next, the protein-protein interaction (PPI) network was constructed. The confidence score cutoff was set at 0.1, and other settings were set to default. 2.4 Gene Ontology functional analysis Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses were performed to assess gene function and biological pathways using the gene symbols of these ten SIGMAR1-related targets in the Metascape platform for comprehensive gene list annotation and analysis, with visualization exports ( http://metascape.prg/gp/index.html ) [ 14 ]. The significance level was set as a P value of < 0.05. 2.5 Construction of SIGMAR1 silencing HN12 cell line In this study, the human HN12 oral squamous carcinoma cell line [ 15 ], and human oral keratinocytes (derived from non-tumor tissue) spontaneously immortalized (NOK-SI), were used. All cells were maintained in DMEM/F12 medium (Gibco™, Thermo Fisher®, Carlsbad, CA, USA), supplemented with 10% Fetal Bovine Serum (FBS), 100 U/ml penicillin, and 100 µg/ml streptomycin, in a humidified atmosphere with 5% CO₂ at 37ºC. SIGMAR1 silencing was performed using the HN12 cell line and the shRNA vector TRCN0000291305 (NM_005866: GACTTCCTCACCCTCTTCTAT), along with the control Scramble_shRNA (SHC002) from Sigma-Aldrich. The Lentiviral particles were produced by co-transfecting a trans-lentiviral packaging mix with the shRNA transfer vector into HEK293T packaging cells (OpenBiosystems). HN12 cells (both knockdown and control groups) were selected with puromycin (0.75 µg/mL) for 7 days. 2.6 Quantitative real-time PCR (qRT-PCR) Total RNA was extracted from NOK-SI and HN12 cells (knockdown and control group) using the AllPrep DNA/RNA/Protein Mini kit (QIAGEN, Hilden, Germany), following the manufacturer's specifications. RNA concentrations were determined using an ND-1000 spectrophotometer device (NanoDrop 1000 Technologies, Wilmington, DE, USA). The reverse transcription reaction for the synthesis of complementary DNA strands (cDNA) was performed using 100 ng of total RNA and the High-Capacity kit (Applied Biosystems, Foster City, CA, USA) according to the manufacturer's instructions. Relative mRNA expression levels were measured by quantitative PCR using GoTaq® qPCR Master Mix (Promega) kit. Reactions were performed on RealPlex4 (Eppendorf), using the internal control: GAPDH. Data were analyzed using the 2 −ΔΔCT method[ 16 ]. The primer sequences used were SIGMAR1 (forward primer: 5’-AGCTCACCACCTACCTCTTTGG-3’, reverse primer: 5’-ACATGGGCTCCAGCAAGTG-3’), and GAPDH (forward primer: 5’-GACTTCAACAGCGACACCCACTC-3’, reverse primer: 5’-GTCCACCACCCTGTTGCTGTAG-3’. The experiments were carried out in triplicate. 2.7 Western Blot The HN12 cells lines were lysed on ice in RIPA buffer containing freshly added protease inhibitor cocktail (Roche Diagnostics, Branchburg, NJ, USA). Protein extracts (30µg) were size-fractionated by SDS-PAGE and proteins were immunoblotted with anti-SIGMAR1 (dilution 1:1000, cat. no. #HPA018002, Cell Signaling Technology, Danvers, MA). Proteins were normalized with β-actin (cat. no. #4967, Cell Signaling Technology, Danvers, MA). All antibodies were diluted according to manufacturer’s instructions and HRP-conjugated goat anti-rabbit (Santa Cruz Biotechnology, Santa Cruz, CA) was used as a secondary antibody. The results were visualized using an enhanced chemiluminescence detection system (Bio-Rad Laboratories, Inc.), and the relative quantification of protein level was determined using ImageJ® software (National Institutes of Health). The experiments were carried out in triplicate. 2.8 Measurement of mitochondrial membrane potential A JC-1 Mitochondrial Membrane Potential Assay Kit (HY-K0601, MedChemExpress, Shanghai, China) was used to measure mitochondrial membrane potential. HN12 cells were plated at a concentration of 1 × 10 5 cells/well in each well of a six-well plate, and then allowed to adhere to plate walls for 24 h. After, the cells were rinsed with serum-free medium and JC-1 (2 µmol/L) was added, and the cells were incubated for 20 min at 37°C. Subsequently, the cells were washed twice with JC-1 staining buffer. The results were qualitatively analyzed using a fluorescence microscope in accordance with the vendor's instructions. The experiments were carried out in triplicate. 2.9 Measurement of intracellular Ca 2+ Intracellular Ca 2+ measurement using BD™ Calcium Assay Kit as previously described [ 17 ]. Briefly, 50,000 HN12 cells/well were plated the day before the experiment. After 24 hours in cell culture incubators 100 µl/well of cell suspension 1 X Dye-loading Solutionwere added to each well and plates incubated with dye for 1 hour at 37C. For this assay we used the following wavelength parameters: Excitation: 485 nm, Emission: 525 nm and AutoCutoff: on (515 nm). The results were obtained through a SpectraMax® L Microplate Reader device. The results were shown as mean from each condition analyzed in triplicate. 2.10 Colony formation assay 1 × 10 4 HN12 cells (knockdown and control group) were plated into 24-well (CORNING) culture plates. They remained in culture for ten days. Next, the colonies were fixed in a methanol-acetic acid (3:1) solution for 15 minutes, washed with PBS and stained with a 0.1% crystal violet solution and colonies were photographed. Quantification of cell colonies was done using ImageJ® software (National Institutes of Health). The colonies numbers were recorded and normalized to the number of colonies in the control group. The results were shown as mean from each condition analyzed in triplicate. 2.11 Statistical analysis The experiments were repeated at least three biological triplicates. The statistical analysis was conducted using Student’s t test (two-tailed) analysis of variance. All results are shown as mean and standard deviation, and P values < 0.05 indicated a significant difference. Analysis and graphical presentation were performed using the GraphPad 8.0 software (San Diego, CA, USA). 3 Results 3.1 Pan-Cancer analysis revealed SIGMAR1 overexpressed with a prognostic significance value for oral cancer Analysis of TCGA data reveals that SIGMAR1 is overexpressed in various cancers, including OC, with significant p-values indicating strong correlations (e.g., HNSCC, p < 0.001). Kaplan-Meier survival analysis of OC patients (n = 335) shows that high SIGMAR1 expression is associated with significantly poorer overall survival compared to low expression levels (p = 0.013). These findings suggest that SIGMAR1 may have prognostic value in OC. 3.2 The HN12 human oral cancer cell line exhibits overexpression of SIGMAR1 We initially examined the SIGMAR1 expression profile using quantitative PCR in two cell lines: spontaneously immortalized normal oral keratinocytes derived from human oral mucosa (NOK-SI) and the HN12 human oral cancer cell line. The results revealed a notable increase in SIGMAR1 mRNA levels in HN12 cells compared to NOK-SI cells (Figure. 1C, p < 0.0001). Subsequently, to elucidate the functional role of SIGMAR1 in OC, we opted to focus on the HN12 OC cell line for further investigation. Employing a specific shRNA targeting SIGMAR1 (shRNA_ SIGMAR1 ) along with its respective control (Scramble), we successfully achieved significant reductions in both mRNA and protein levels of SIGMAR1 in the HN12 cells, knockdown group, compared to the control (Scramble) group (Figures. 1D-E, p < 0.0001). 3.3 Downregulation of SIGMAR1 resulted in elevated mitochondrial membrane potential To assess mitochondrial membrane potential (ΔΨm) in OC cells, we used the JC-1 probe, where high ΔΨm indicates healthy mitochondria (red fluorescence) and low ΔΨm indicates damaged mitochondria (green fluorescence). Immunofluorescence analysis revealed that control HN12 cells displayed weak red fluorescence, while SIGMAR1 knockdown HN12 cells showed significantly increased red fluorescence intensity, indicating higher mitochondrial membrane potential (Fig. 2 A). These findings suggest that SIGMAR1 depletion leads to mitochondrial depolarization, impacting the ΔΨm of HN12 cells. 3.4 Knockdown of SIGMAR1 significantly inhibited Ca 2+ influx and clonogenic growth in human oral cancer cells To explore the mechanistic roles of SIGMAR1 and its co-regulated genes, we identified the top 10 predicted targets that interact with SIGMAR1, establishing a protein-protein interaction (PPI) network using the STRING database (PPI enrichment p-value = 0.014, Fig. 2 B). Next, the Gene Ontology (GO) enrichment analysis indicated that SIGMAR1 is involved in the release of sequestered calcium ions into the cytosol (Fig. 2 C). To further investigate SIGMAR1's functional role, we measured Ca²⁺ influx in HN12 oral cancer cells. Our results showed that SIGMAR1 knockdown significantly reduced Ca²⁺ influx in the cytosol compared to control cells (Gigure 2D, p < 0.001). These findings suggest that silencing SIGMAR1 decreases Ca²⁺ influx in human oral cancer cells. Calcium signaling plays fundamental roles in cancer cell survival [ 8 ]. Then, to assess the impact of SIGMAR1 knockdown on cell survival in vitro , we conducted clonogenic assays, revealing a significant reduction in the clonogenic growth of HN12 cells following SIGMAR1 knockdown compared to control cells. Conversely, the SIGMAR1-overexpressing group exhibited a higher number of colonies (Fig. 2 E, p < 0.001). These results suggest that SIGMAR1 overexpression promotes cell survival and enhances clonogenicity by regulating Ca²⁺ influx in OC cells. Overall, this study provides new insights into the role of SIGMAR1 in Ca²⁺ signaling and its involvement in OC progression. 4 Discussion We found that SIGMAR1 is overexpressed in OC compared to normal tissue correlated with poorer prognosis. Of note, studies show its overexpression in myeloid leukemia and colorectal cancer enhances tumor aggressiveness, invasion, and angiogenesis, leading to worse survival [ 18 ]. Additionally, SIGMAR1 is also found overexpressed in specific subtypes of breast cancer, and stands as a promising target for the development of personalized treatments in the next generation of therapeutic approaches[ 19 ]. Overall, our findings suggest that SIGMAR1 holds promise as a novel biomarker worthy of further exploration in the context of OC. Next, to shed light on the function of SIGMAR1 in OC, we conducted SIGMAR1 silencing experiments using an in vitro model of OC. Taken together, our findings demonstrate that blocking SIGMAR1 not only leads to an increase in mitochondrial membrane potential but also reduces cytosolic calcium influx. Consequently, inhibition of SIGMAR1 caused profound impairment in cancer cell proliferation as evaluated by clonogenic growth assays. Cellular mitochondrial calcium dynamics are complicated processes regulating how the levels of calcium ions within a cell can be controlled, received and released, and most importantly when and how they can be used[ 20 ]. They form the basis of several very important processes in cell metabolism, signal transmitting and regulated cell death (apoptosis) [ 21 ]. Mitochondria have specialized calcium transport systems, including the mitochondrial calcium uniporter (MCU) complex, which facilitates the entry of calcium ions from the cytoplasm into the mitochondrial matrix. Once inside, calcium ions interact with mitochondrial proteins and enzymes, regulating mitochondrial function. Besides, calcium levels within mitochondria are tightly controlled through mechanisms that balance influx and efflux. However, disruptions in mitochondrial calcium cycling can lead to significant cellular dysfunction, negatively impacting physiological processes and exacerbating pathological conditions[ 22 ]. However, disruption of calcium levels of mitochondria is often linked to development of several diseases, as exemple, cancer[ 23 ]. Our study revealed that blocking SIGMAR1 significantly increased mitochondrial membrane potential while reducing cytosolic calcium influx. Consequently, inhibiting SIGMAR1 led to a marked decrease in clonogenic growth in our in vitro model, highlighting its crucial role in OC development and progression. Interestingly, control cells exhibited reduced mitochondrial membrane potential, a known marker for cancer cell radioresistance. This finding underscores the potential of SIGMAR1 as a therapeutic target in improving treatment responses for OC[ 24 ]. This is important, because OC poses a significant challenge in treatment due to the development of radioresistance, which can lead to tumor relapse and metastasis post-radiotherapy [ 25 ]. Althougth the relationship between altered mitochondrial membrane potential and calcium influx is complex and multifaceted, molecular studies indicate that mitochondrial membrane potential plays a crucial role in modulating calcium influx, as shown in skeletal muscle cells, human fibroblasts, and neurons [ 26 – 28 ]. Overall, These findings suggest that maintaining mitochondrial membrane potential is vital for regulating calcium dynamics within cells. Mitochondria play a crucial role in calcium homeostasis, and alterations in their mitochondrial membrane potential can influence calcium dynamics (maintaining calcium homeostasis) within the cell [ 29 ]. A reduction in mitochondrial membrane potential can disrupt calcium homeostasis, resulting in elevated cytoplasmic calcium levels that affect calcium-dependent signaling pathways and various cellular processes. For example, loss of mitochondrial membrane potential is associated with mitochondrial dysfunction, which impairs the mitochondria's ability to uptake calcium effectively. This dysregulation can further contribute to cellular disturbances and impact overall cell health [ 30 ]. Therefore, we suggest that decreased membrane potential observed in the OC cells (control group), may disrupt calcium handling by mitochondria, leading to aberrant calcium signaling within cancer cells. Conversely, dysregulated calcium signaling can impact various cellular processes, including cell proliferation, apoptosis, and metabolism[ 31 ]. Then, we propose that a higher mitochondrial membrane potential enhances calcium retention within the mitochondrial matrix, leading to decreased concentrations of free calcium ions in the cytoplasm in OC cells. Consequentlly, this reduction may subsequently lower calcium influx from the extracellular space or other intracellular calcium stores in OC cells. Calcium signaling is also involved in regulating key checkpoints in the cell cycle [ 32 ]. Decreased calcium signaling can disrupt these checkpoints, leading to cell cycle arrest and inhibition of cell proliferation [ 33 ]. It was recently demonstrated in vivo , that the knockdown of SIGMAR1 reduced the Ca 2+ influx in cardiomyocytes [ 34 ]. Furthermore, knockdown of SIGMAR1 not only reduced intracellular calcium levels but also reduced breast and colorectal cancer cell migration [ 19 ]. In such circumstances, we hypothesized that reduction of calcium transmission in the OC cells possibly disables the cell’s ability to replicate and proliferate effectively, as observed in OC cells (SIGMAR1 knockdown group). Besides, is important to highlight that the disruption of calcium homeostasis contributes to development of cancer [ 35 ]. However, although the role of calcium signaling in OC development and progression is complex, we suggest that SIGMAR1 plays specific functions in the modulation of intracellular calcium levels, and this has a significant impact on cancer cell proliferation. Besides, it is important to note that the relationship between calcium signaling and cancer is highly context-dependent and can vary depending on the specific type of cancer, as well as other factors such as the tumor microenvironment and genetic mutations. 5 Conclusion In summary, we demonstrated that SIGMAR1 knockdown affects key cellular processes, including mitochondrial function, calcium homeostasis, and clonogenic growth. Our findings suggest that SIGMAR1 contributes to OC pathogenesis by influencing mitochondrial calcium dynamics and decrease cell clonogenic growth. However, further investigation into the mechanisms underlying SIGMAR1's role in OC and its therapeutic implications is crucial for enhancing our understanding and developing effective treatment strategies for this challenging disease. Declarations Consent for Publication: Not applicable. Conflicts of Interest: All authors declare that they had no conflict of interest that could be perceived to impair the impartiality of the reported research. Ethics approval and consent to participate: Not applicable. Funding: The study was supported by public Brazilian grants from the São Paulo State Research Foundation (FAPESP), Grant numbers: 2016/19103-2, 2021/03732-9, 2022/07821-9. Author Contribution All authors had full access to all data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: P.S.C designed, conducted, interpreted all experiments, drafted, and critically read the manuscript. C.S.B.G and H.I.S , provided laboratory assistance and critically revised the manuscript. W.A.Y and B.B helped discuss the results, edited the manuscript, and provided critical comments. A.M.L was responsible for the supervision, helped with concept and design, provided critical comments, edited, and revised the text for important intellectual content. All authors gave their final approval and agreed to be accountable for all aspects of the work. Acknowledgement We are grateful to Dr. J. Silvio Gutkind (UC San Diego, CA, USA) who kindly provided the NOK-SI cell line for the study. Data availability statement: The data presented in this study are available in this article. Additionally, other items that support the results of the study will be made available upon reasonable request. References References : Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A (2024) Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin Eskander A, Dziegielewski PT, Patel MR, Jethwa AR, Pai PS, Silver NL, Sajisevi M, Sanabria A, Doweck I, Khariwala SS (2024) St John M. 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Cite Share Download PDF Status: Published Journal Publication published 11 Feb, 2025 Read the published version in Molecular Biology Reports → Version 1 posted Editorial decision: Revision requested 03 Dec, 2024 Reviews received at journal 30 Nov, 2024 Reviews received at journal 26 Nov, 2024 Reviews received at journal 26 Nov, 2024 Reviewers agreed at journal 16 Nov, 2024 Reviewers agreed at journal 13 Nov, 2024 Reviewers agreed at journal 11 Nov, 2024 Reviewers agreed at journal 11 Nov, 2024 Reviewers invited by journal 28 Oct, 2024 Editor assigned by journal 26 Oct, 2024 Submission checks completed at journal 26 Oct, 2024 First submitted to journal 25 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5333239","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":372461961,"identity":"2b4213aa-f16c-475b-aa4d-263978c4ce62","order_by":0,"name":"Pablo Shimaoka Chagas","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYFACHsYDDAwHQCzGByDSgAgtDDAtzAYka2GTIEqLOfvZAwc+1NyRl3c//qya588dBnPpA/i1WPbkJRycceyZ4cYzOWa3edueMVj2JeDXYnAgx+Awb8Nhxo0NOWy3gQwGgzMEHGZw/g1Yi/3G/ufPinn+EKPlBsSWxPkSCWbMPGxEaLGc8Q7kl8PJGyTeGEvObXvGY9lDQIs5f+7BBx9qDtvO709/+OHNnzty5jyEHAZnHABTBwhpQNIi3wDRQlDHKBgFo2AUjDwAAF/MTpx2C8pNAAAAAElFTkSuQmCC","orcid":"","institution":"University of São Paulo","correspondingAuthor":true,"prefix":"","firstName":"Pablo","middleName":"Shimaoka","lastName":"Chagas","suffix":""},{"id":372461964,"identity":"6159cc2a-3167-40e5-b49f-89a47da185aa","order_by":1,"name":"Cristiana Bernadelli Garcia","email":"","orcid":"","institution":"University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Cristiana","middleName":"Bernadelli","lastName":"Garcia","suffix":""},{"id":372461968,"identity":"5c228272-8f8b-4cbc-9850-ed6a9c18f1ad","order_by":2,"name":"Henrique Izumi Shimaoka Chagas","email":"","orcid":"","institution":"Augusta University","correspondingAuthor":false,"prefix":"","firstName":"Henrique","middleName":"Izumi Shimaoka","lastName":"Chagas","suffix":""},{"id":372461970,"identity":"6d2257e0-190b-42ca-891a-f576d1703efc","order_by":3,"name":"William Andrew Yeudall","email":"","orcid":"","institution":"Augusta University","correspondingAuthor":false,"prefix":"","firstName":"William","middleName":"Andrew","lastName":"Yeudall","suffix":""},{"id":372461973,"identity":"d12ce9b9-8f5f-4523-a305-a6598c8c2d8b","order_by":4,"name":"Jack C Yu","email":"","orcid":"","institution":"Augusta University","correspondingAuthor":false,"prefix":"","firstName":"Jack","middleName":"C","lastName":"Yu","suffix":""},{"id":372461975,"identity":"485c1661-09ac-4353-abc7-17c51c91fc8d","order_by":5,"name":"Babak Baban","email":"","orcid":"","institution":"Augusta University","correspondingAuthor":false,"prefix":"","firstName":"Babak","middleName":"","lastName":"Baban","suffix":""},{"id":372461979,"identity":"1c636621-cdd0-4cd8-b0cf-599e26217212","order_by":6,"name":"Andréia Machado Leopoldino","email":"","orcid":"","institution":"University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Andréia","middleName":"Machado","lastName":"Leopoldino","suffix":""}],"badges":[],"createdAt":"2024-10-25 14:53:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5333239/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5333239/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11033-025-10336-2","type":"published","date":"2025-02-11T15:58:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":69081346,"identity":"e0bf83fb-ea25-4fdf-a2d0-67b11c2be5e0","added_by":"auto","created_at":"2024-11-15 12:01:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":24031196,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUpregulated mRNA expression of SIGMAR1 in pan-cancer analysis reveals its prognostic value. \u003c/strong\u003e(A) The mRNA levels of the \u003cem\u003eSIGMAR1\u003c/em\u003e gene were analyzed through TIMER2.0 and was markedly increased in 18 cancer types using TCGA data. The red and blue boxes represent tumor and normal tissues, respectively. *\u003cem\u003ep \u003c/em\u003e\u0026lt;0.05; **\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.01; ***\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001. (B) Kaplan-Meier survival curves show worse prognosis associated with high expression of \u003cem\u003eSIGMAR1\u003c/em\u003e in patients with OC (n=335) based on the TCGA cohort, \u003cem\u003ep\u003c/em\u003e=0.013. (C) Relative expression of mRNA \u003cem\u003eSIGMAR1\u003c/em\u003e levels in NOK-SI and HN12 cell lines by RT-qPCR. The graph shows the mean ± standard deviation of three independent experiments (*\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). (D) Relative expression of mRNA \u003cem\u003eSIGMAR1\u003c/em\u003e levels in Scramble_HN12 cells and shRNA_\u003cem\u003eSIGMRA1\u003c/em\u003e cells, respectively, by RT-qPCR. The graph shows the mean ± standard deviation of three independent experiments (*\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). (E) Western blot and protein relative quantification of SIGMAR1 in Scramble_HN12 cells and shRNA_\u003cem\u003eSIGMRA1\u003c/em\u003e cells, respectively. Relative protein quantification was performed by using \u003cem\u003eImageJ\u003c/em\u003e software. Β-actin protein was used as an endogenous control.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5333239/v1/6eb2a84298ca2fee2e4d97b3.png"},{"id":69081347,"identity":"fa597f65-bdd3-4565-8ee1-7b0fd6daf8c1","added_by":"auto","created_at":"2024-11-15 12:01:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":44817342,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eUnraveling \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eSIGMAR1\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e knockdown: implications on mitochondrial calcium dynamics in oral cancer cells. \u003c/strong\u003e(A) Representative images of mitochondrial membrane potential in HN12 oral cancer cell line, after \u003cem\u003eSIGMAR1\u003c/em\u003e knockdown, as revealed by JC-1 staining. Bar=100 μm. The images showing the fluorescence of MMP were captured following incubation with JC-1. The alteration in fluorescence emission, transitioning from green (JC-1 monomers) to red (JC-1 aggregates) indicates changes in ∆ψm. (B) PPI analysis reveals interactions potential of SIGMAR1 and its coregulated genes. Circles represent genes and the results within the circle represent the structure of proteins. Lines colors represent evidence of the interaction of proteins between genes: genetic interactions (line in blue), co-expression (line in purple), gene neighborhood (line in green). (C) Gene ontology (GO) enrichment analysis (biological process) of SIGMAR1-coregulated genes. Significantly enriched GO terms are shown with Benjamini-Hochberg FDR-corrected \u003cem\u003ep\u003c/em\u003e-values. (D) The intracellular Ca\u003csup\u003e2+\u003c/sup\u003e homeostasis was decreased in \u003cem\u003eSIGMAR1\u003c/em\u003e shRNA HN12 cell line compared to control (shRNA Scramble). (E) The digital images of cell colonies and respective quantification analysis of the colonies. Data were shown as mean ± SD.*\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001. The \u003cem\u003eSIGMAR1\u003c/em\u003e silencing decreased the number of cell colonies in \u003cem\u003eSIGMAR1\u003c/em\u003e shRNA HN12 cell line compared to control (shRNA Scramble). Relative cell colonies quantification was performed by using \u003cem\u003eImageJ\u003c/em\u003e software.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5333239/v1/c2b2ccdf0a4b58e9e5583b76.png"},{"id":76488154,"identity":"146ac243-1b2c-47fb-b7d3-72a8b8cec3bb","added_by":"auto","created_at":"2025-02-17 16:13:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":66467011,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5333239/v1/76150a62-d6ee-42e0-8079-2d4a618515c3.pdf"},{"id":69081344,"identity":"259c8da0-2273-47bd-87b2-6d0ba37ae47b","added_by":"auto","created_at":"2024-11-15 12:01:54","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":437369,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGraphical abstract: \u003c/strong\u003eIn oral cancer cells, overexpression of SIGMAR1 leads to heightened calcium influx and damage to the mitochondrial membrane potential, thereby elevating cytosolic calcium levels. Conversely, knockdown of SIGMAR1 enhances mitochondrial membrane potential, resulting in decreased cytosolic calcium levels and reduced cell survival capacity.\u003c/p\u003e","description":"","filename":"GA.png","url":"https://assets-eu.researchsquare.com/files/rs-5333239/v1/a10df278b53614487595504a.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Suppression of SIGMAR1 hinders oral cancer cell growth via modulation of mitochondrial Ca2+ dynamics","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eGlobally, approximately 390,000 new cases of Oral Cancer (OC) are diagnosed annually, contributing to a significant health burden[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Of note, the OC primarily originates from the squamous cells lining the oral cavity, including the lips, tongue, gums, floor of the mouth, palate, and oropharynx [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Beyond that, the major risk factors of OC include use of tobacco, heavy alcohol consumption, betel nut chewing and HPV infection [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. However, the diagnosis of OC typically involves a physical exam, biopsy, and imaging tests and, the treatment depends on the tumor's stage and location and may include surgery, radiation, chemotherapy, or adjuvant therapy. On the other hand, the prognosis varies based on the stage at diagnosis[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Despite this, the 5-year overall survival (OS) rate is below 65%, with high recurrence and metastasis rates [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Thus, the conventional treatments for OC face challenges such as tumor heterogeneity, treatment resistance, and adverse side effects, limiting their effectiveness in reducing tumor growth. In this conecction, the discovery of new biomarkers for OC therapy is crucial to advancing treatment options and improving patient outcomes.\u003c/p\u003e \u003cp\u003eEmerging research identifies the Sigma-1 receptor (SIGMAR1) as a key factor in cancer biology, with roles in cellular pathophysiology, survival, and signaling, making it a promising target for cancer therapy [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Significantly, SIGMAR1 is a protein located in the endoplasmic reticulum (ER), where it regulates various cellular processes, including mitochondrial functions and calcium signaling [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This is highly relevant as it suggests that mitochondrial dysfunction contributes to the upregulation of calcium signaling, a key driver of cancer cell growth, progression, and various aspects of tumor development, including cellular metabolism and signaling [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Conversely, abnormalities in this delicate balance can impact cancer cell survival and tumor progression [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, it remains unclear whether the SIGMAR1 receptor influences the regulation of mitochondrial function and calcium signaling in OC and whether it affects cancer cell survival.\u003c/p\u003e \u003cp\u003eThis study aimed to evaluate the effects of SIGMAR1 knockdown in OC cells, focusing on mitochondrial function, calcium homeostasis, and clonogenic growth. Our initial findings revealed that SIGMAR1 is significantly overexpressed in OC compared to normal tissue, and this upregulation correlates with poorer disease prognosis. Of note, SIGMAR1 silencing increased mitochondrial membrane potential and reduced cytosolic calcium influx, leading to a marked decrease in colony formation by the cells. Overall,for the first time, we suggest that SIGMAR1 may influence mitochondrial membrane potential and energy production by modulating Ca\u0026sup2;⁺ uptake, making it critical for cellular survival.\u003c/p\u003e"},{"header":"2 Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Integrative Pan-Cancer Analysis\u003c/h2\u003e \u003cp\u003eWe used the Tumor Immune Estimation Resource (TIMER) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cistrome.shinyapps.io/timer/\u003c/span\u003e\u003cspan address=\"https://cistrome.shinyapps.io/timer/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] to identify the differential expression levels of \u003cem\u003eSIGMAR1\u003c/em\u003e (tumor \u003cem\u003evs.\u003c/em\u003e matched normal tissues) in 23 different malignant tumors from the TCGA project.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Evaluation of the survival analysis\u003c/h2\u003e \u003cp\u003eThe prognostic significance of the \u003cem\u003eSIGMAR1\u003c/em\u003e in OC samples was evaluated using the Kaplan\u0026ndash;Meier Plotter tool available on R2: Genomics Analysis and Visualization Platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://r2.amc.nl\u003c/span\u003e\u003cspan address=\"http://r2.amc.nl\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), database (accessed on 09/15/2024). The \u003cem\u003ep-value\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicates statistical significance.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Network construction: Protein-Protein Interaction of SIGMAR1\u003c/h2\u003e \u003cp\u003eThe STRING tool, v.11.0, (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://string-db.org/\u003c/span\u003e\u003cspan address=\"https://string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], was used to create a Homo Sapiens SIGMAR1 co-expression network. Next, the protein-protein interaction (PPI) network was constructed. The confidence score cutoff was set at 0.1, and other settings were set to default.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Gene Ontology functional analysis\u003c/h2\u003e \u003cp\u003eGene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses were performed to assess gene function and biological pathways using the gene symbols of these ten SIGMAR1-related targets in the Metascape platform for comprehensive gene list annotation and analysis, with visualization exports (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://metascape.prg/gp/index.html\u003c/span\u003e\u003cspan address=\"http://metascape.prg/gp/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e)\u003c/span\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The significance level was set as a \u003cem\u003eP\u003c/em\u003e value of \u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Construction of \u003cem\u003eSIGMAR1\u003c/em\u003e silencing HN12 cell line\u003c/h2\u003e \u003cp\u003eIn this study, the human HN12 oral squamous carcinoma cell line [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], and human oral keratinocytes (derived from non-tumor tissue) spontaneously immortalized (NOK-SI), were used. All cells were maintained in DMEM/F12 medium (Gibco\u0026trade;, Thermo Fisher\u0026reg;, Carlsbad, CA, USA), supplemented with 10% Fetal Bovine Serum (FBS), 100 U/ml penicillin, and 100 \u0026micro;g/ml streptomycin, in a humidified atmosphere with 5% CO₂ at 37\u0026ordm;C. SIGMAR1 silencing was performed using the HN12 cell line and the shRNA vector TRCN0000291305 (NM_005866: GACTTCCTCACCCTCTTCTAT), along with the control Scramble_shRNA (SHC002) from Sigma-Aldrich. The Lentiviral particles were produced by co-transfecting a trans-lentiviral packaging mix with the shRNA transfer vector into HEK293T packaging cells (OpenBiosystems). HN12 cells (both knockdown and control groups) were selected with puromycin (0.75 \u0026micro;g/mL) for 7 days.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Quantitative real-time PCR (qRT-PCR)\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted from NOK-SI and HN12 cells (knockdown and control group) using the AllPrep DNA/RNA/Protein Mini kit (QIAGEN, Hilden, Germany), following the manufacturer's specifications. RNA concentrations were determined using an ND-1000 spectrophotometer device (NanoDrop 1000 Technologies, Wilmington, DE, USA). The reverse transcription reaction for the synthesis of complementary DNA strands (cDNA) was performed using 100 ng of total RNA and the High-Capacity kit (Applied Biosystems, Foster City, CA, USA) according to the manufacturer's instructions. Relative mRNA expression levels were measured by quantitative PCR using GoTaq\u0026reg; qPCR Master Mix (Promega) kit. Reactions were performed on RealPlex4 (Eppendorf), using the internal control: GAPDH. Data were analyzed using the 2\u003csup\u003e\u0026minus;ΔΔCT\u003c/sup\u003e method[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The primer sequences used were \u003cem\u003eSIGMAR1\u003c/em\u003e (forward primer: 5\u0026rsquo;-AGCTCACCACCTACCTCTTTGG-3\u0026rsquo;, reverse primer: 5\u0026rsquo;-ACATGGGCTCCAGCAAGTG-3\u0026rsquo;), and \u003cem\u003eGAPDH\u003c/em\u003e (forward primer: 5\u0026rsquo;-GACTTCAACAGCGACACCCACTC-3\u0026rsquo;, reverse primer: 5\u0026rsquo;-GTCCACCACCCTGTTGCTGTAG-3\u0026rsquo;. The experiments were carried out in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Western Blot\u003c/h2\u003e \u003cp\u003eThe HN12 cells lines were lysed on ice in RIPA buffer containing freshly added protease inhibitor cocktail (Roche Diagnostics, Branchburg, NJ, USA). Protein extracts (30\u0026micro;g) were size-fractionated by SDS-PAGE and proteins were immunoblotted with anti-SIGMAR1 (dilution 1:1000, cat. no. #HPA018002, Cell Signaling Technology, Danvers, MA). Proteins were normalized with β-actin (cat. no. #4967, Cell Signaling Technology, Danvers, MA). All antibodies were diluted according to manufacturer\u0026rsquo;s instructions and HRP-conjugated goat anti-rabbit (Santa Cruz Biotechnology, Santa Cruz, CA) was used as a secondary antibody. The results were visualized using an enhanced chemiluminescence detection system (Bio-Rad Laboratories, Inc.), and the relative quantification of protein level was determined using ImageJ\u0026reg; software (National Institutes of Health). The experiments were carried out in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Measurement of mitochondrial membrane potential\u003c/h2\u003e \u003cp\u003eA JC-1 Mitochondrial Membrane Potential Assay Kit (HY-K0601, MedChemExpress, Shanghai, China) was used to measure mitochondrial membrane potential. HN12 cells were plated at a concentration of 1 \u0026times; 10\u003csup\u003e5\u003c/sup\u003e cells/well in each well of a six-well plate, and then allowed to adhere to plate walls for 24 h. After, the cells were rinsed with serum-free medium and JC-1 (2 \u0026micro;mol/L) was added, and the cells were incubated for 20 min at 37\u0026deg;C. Subsequently, the cells were washed twice with JC-1 staining buffer. The results were qualitatively analyzed using a fluorescence microscope in accordance with the vendor's instructions. The experiments were carried out in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Measurement of intracellular Ca\u003csup\u003e2+\u003c/sup\u003e\u003c/h2\u003e \u003cp\u003eIntracellular Ca\u003csup\u003e2+\u003c/sup\u003e measurement using BD\u0026trade; Calcium Assay Kit as previously described [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Briefly, 50,000 HN12 cells/well were plated the day before the experiment. After 24 hours in cell culture incubators 100 \u0026micro;l/well of cell suspension 1 X Dye-loading Solutionwere added to each well and plates incubated with dye for 1 hour at 37C. For this assay we used the following wavelength parameters: Excitation: 485 nm, Emission: 525 nm and AutoCutoff: on (515 nm). The results were obtained through a SpectraMax\u0026reg; L Microplate Reader device. The results were shown as mean from each condition analyzed in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Colony formation assay\u003c/h2\u003e \u003cp\u003e1 \u0026times; 10 \u003csup\u003e4\u003c/sup\u003e HN12 cells (knockdown and control group) were plated into 24-well (CORNING) culture plates. They remained in culture for ten days. Next, the colonies were fixed in a methanol-acetic acid (3:1) solution for 15 minutes, washed with PBS and stained with a 0.1% crystal violet solution and colonies were photographed. Quantification of cell colonies was done using ImageJ\u0026reg; software (National Institutes of Health). The colonies numbers were recorded and normalized to the number of colonies in the control group. The results were shown as mean from each condition analyzed in triplicate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.11 Statistical analysis\u003c/h2\u003e \u003cp\u003eThe experiments were repeated at least three biological triplicates. The statistical analysis was conducted using Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e test (two-tailed) analysis of variance. All results are shown as mean and standard deviation, and \u003cem\u003eP\u003c/em\u003e values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicated a significant difference. Analysis and graphical presentation were performed using the GraphPad 8.0 software (San Diego, CA, USA).\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Pan-Cancer analysis revealed \u003cem\u003eSIGMAR1\u003c/em\u003e overexpressed with a prognostic significance value for oral cancer\u003c/h2\u003e \u003cp\u003eAnalysis of TCGA data reveals that \u003cem\u003eSIGMAR1\u003c/em\u003e is overexpressed in various cancers, including OC, with significant p-values indicating strong correlations (e.g., HNSCC, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Kaplan-Meier survival analysis of OC patients (n\u0026thinsp;=\u0026thinsp;335) shows that high \u003cem\u003eSIGMAR1\u003c/em\u003e expression is associated with significantly poorer overall survival compared to low expression levels (p\u0026thinsp;=\u0026thinsp;0.013). These findings suggest that SIGMAR1 may have prognostic value in OC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.2 The HN12 human oral cancer cell line exhibits overexpression of SIGMAR1\u003c/h2\u003e \u003cp\u003eWe initially examined the \u003cem\u003eSIGMAR1\u003c/em\u003e expression profile using quantitative PCR in two cell lines: spontaneously immortalized normal oral keratinocytes derived from human oral mucosa (NOK-SI) and the HN12 human oral cancer cell line. The results revealed a notable increase in \u003cem\u003eSIGMAR1\u003c/em\u003e mRNA levels in HN12 cells compared to NOK-SI cells (Figure. 1C, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Subsequently, to elucidate the functional role of SIGMAR1 in OC, we opted to focus on the HN12 OC cell line for further investigation. Employing a specific shRNA targeting \u003cem\u003eSIGMAR1\u003c/em\u003e (shRNA_\u003cem\u003eSIGMAR1\u003c/em\u003e) along with its respective control (Scramble), we successfully achieved significant reductions in both mRNA and protein levels of SIGMAR1 in the HN12 cells, knockdown group, compared to the control (Scramble) group (Figures. 1D-E, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Downregulation of \u003cem\u003eSIGMAR1\u003c/em\u003e resulted in elevated mitochondrial membrane potential\u003c/h2\u003e \u003cp\u003eTo assess mitochondrial membrane potential (ΔΨm) in OC cells, we used the JC-1 probe, where high ΔΨm indicates healthy mitochondria (red fluorescence) and low ΔΨm indicates damaged mitochondria (green fluorescence). Immunofluorescence analysis revealed that control HN12 cells displayed weak red fluorescence, while SIGMAR1 knockdown HN12 cells showed significantly increased red fluorescence intensity, indicating higher mitochondrial membrane potential (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). These findings suggest that SIGMAR1 depletion leads to mitochondrial depolarization, impacting the ΔΨm of HN12 cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.4 \u003cb\u003eKnockdown of\u003c/b\u003e \u003cb\u003eSIGMAR1\u003c/b\u003e \u003cb\u003esignificantly inhibited Ca\u003c/b\u003e\u003csup\u003e\u003cb\u003e2+\u003c/b\u003e\u003c/sup\u003e \u003cb\u003einflux and clonogenic growth in human oral cancer cells\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eTo explore the mechanistic roles of SIGMAR1 and its co-regulated genes, we identified the top 10 predicted targets that interact with SIGMAR1, establishing a protein-protein interaction (PPI) network using the STRING database (PPI enrichment p-value\u0026thinsp;=\u0026thinsp;0.014, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Next, the Gene Ontology (GO) enrichment analysis indicated that SIGMAR1 is involved in the release of sequestered calcium ions into the cytosol (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). To further investigate SIGMAR1's functional role, we measured Ca\u0026sup2;⁺ influx in HN12 oral cancer cells. Our results showed that SIGMAR1 knockdown significantly reduced Ca\u0026sup2;⁺ influx in the cytosol compared to control cells (Gigure 2D, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These findings suggest that silencing SIGMAR1 decreases Ca\u0026sup2;⁺ influx in human oral cancer cells. Calcium signaling plays fundamental roles in cancer cell survival [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Then, to assess the impact of SIGMAR1 knockdown on cell survival \u003cem\u003ein vitro\u003c/em\u003e, we conducted clonogenic assays, revealing a significant reduction in the clonogenic growth of HN12 cells following SIGMAR1 knockdown compared to control cells. Conversely, the SIGMAR1-overexpressing group exhibited a higher number of colonies (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). These results suggest that SIGMAR1 overexpression promotes cell survival and enhances clonogenicity by regulating Ca\u0026sup2;⁺ influx in OC cells. Overall, this study provides new insights into the role of SIGMAR1 in Ca\u0026sup2;⁺ signaling and its involvement in OC progression.\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eWe found that \u003cem\u003eSIGMAR1\u003c/em\u003e is overexpressed in OC compared to normal tissue correlated with poorer prognosis. Of note, studies show its overexpression in myeloid leukemia and colorectal cancer enhances tumor aggressiveness, invasion, and angiogenesis, leading to worse survival [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Additionally, SIGMAR1 is also found overexpressed in specific subtypes of breast cancer, and stands as a promising target for the development of personalized treatments in the next generation of therapeutic approaches[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Overall, our findings suggest that SIGMAR1 holds promise as a novel biomarker worthy of further exploration in the context of OC. Next, to shed light on the function of SIGMAR1 in OC, we conducted SIGMAR1 silencing experiments using an \u003cem\u003ein vitro\u003c/em\u003e model of OC. Taken together, our findings demonstrate that blocking SIGMAR1 not only leads to an increase in mitochondrial membrane potential but also reduces cytosolic calcium influx. Consequently, inhibition of SIGMAR1 caused profound impairment in cancer cell proliferation as evaluated by clonogenic growth assays.\u003c/p\u003e \u003cp\u003eCellular mitochondrial calcium dynamics are complicated processes regulating how the levels of calcium ions within a cell can be controlled, received and released, and most importantly when and how they can be used[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. They form the basis of several very important processes in cell metabolism, signal transmitting and regulated cell death (apoptosis) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Mitochondria have specialized calcium transport systems, including the mitochondrial calcium uniporter (MCU) complex, which facilitates the entry of calcium ions from the cytoplasm into the mitochondrial matrix. Once inside, calcium ions interact with mitochondrial proteins and enzymes, regulating mitochondrial function. Besides, calcium levels within mitochondria are tightly controlled through mechanisms that balance influx and efflux. However, disruptions in mitochondrial calcium cycling can lead to significant cellular dysfunction, negatively impacting physiological processes and exacerbating pathological conditions[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, disruption of calcium levels of mitochondria is often linked to development of several diseases, as exemple, cancer[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study revealed that blocking SIGMAR1 significantly increased mitochondrial membrane potential while reducing cytosolic calcium influx. Consequently, inhibiting SIGMAR1 led to a marked decrease in clonogenic growth in our \u003cem\u003ein vitro\u003c/em\u003e model, highlighting its crucial role in OC development and progression. Interestingly, control cells exhibited reduced mitochondrial membrane potential, a known marker for cancer cell radioresistance. This finding underscores the potential of SIGMAR1 as a therapeutic target in improving treatment responses for OC[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This is important, because OC poses a significant challenge in treatment due to the development of radioresistance, which can lead to tumor relapse and metastasis post-radiotherapy [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Althougth the relationship between altered mitochondrial membrane potential and calcium influx is complex and multifaceted, molecular studies indicate that mitochondrial membrane potential plays a crucial role in modulating calcium influx, as shown in skeletal muscle cells, human fibroblasts, and neurons [\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Overall, These findings suggest that maintaining mitochondrial membrane potential is vital for regulating calcium dynamics within cells.\u003c/p\u003e \u003cp\u003eMitochondria play a crucial role in calcium homeostasis, and alterations in their mitochondrial membrane potential can influence calcium dynamics (maintaining calcium homeostasis) within the cell [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. A reduction in mitochondrial membrane potential can disrupt calcium homeostasis, resulting in elevated cytoplasmic calcium levels that affect calcium-dependent signaling pathways and various cellular processes. For example, loss of mitochondrial membrane potential is associated with mitochondrial dysfunction, which impairs the mitochondria's ability to uptake calcium effectively. This dysregulation can further contribute to cellular disturbances and impact overall cell health [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Therefore, we suggest that decreased membrane potential observed in the OC cells (control group), may disrupt calcium handling by mitochondria, leading to aberrant calcium signaling within cancer cells. Conversely, dysregulated calcium signaling can impact various cellular processes, including cell proliferation, apoptosis, and metabolism[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Then, we propose that a higher mitochondrial membrane potential enhances calcium retention within the mitochondrial matrix, leading to decreased concentrations of free calcium ions in the cytoplasm in OC cells. Consequentlly, this reduction may subsequently lower calcium influx from the extracellular space or other intracellular calcium stores in OC cells.\u003c/p\u003e \u003cp\u003eCalcium signaling is also involved in regulating key checkpoints in the cell cycle [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Decreased calcium signaling can disrupt these checkpoints, leading to cell cycle arrest and inhibition of cell proliferation [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. It was recently demonstrated \u003cem\u003ein vivo\u003c/em\u003e, that the knockdown of SIGMAR1 reduced the Ca\u003csup\u003e2+\u003c/sup\u003e influx in cardiomyocytes [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Furthermore, knockdown of SIGMAR1 not only reduced intracellular calcium levels but also reduced breast and colorectal cancer cell migration [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In such circumstances, we hypothesized that reduction of calcium transmission in the OC cells possibly disables the cell\u0026rsquo;s ability to replicate and proliferate effectively, as observed in OC cells (SIGMAR1 knockdown group).\u003c/p\u003e \u003cp\u003eBesides, is important to highlight that the disruption of calcium homeostasis contributes to development of cancer [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. However, although the role of calcium signaling in OC development and progression is complex, we suggest that SIGMAR1 plays specific functions in the modulation of intracellular calcium levels, and this has a significant impact on cancer cell proliferation. Besides, it is important to note that the relationship between calcium signaling and cancer is highly context-dependent and can vary depending on the specific type of cancer, as well as other factors such as the tumor microenvironment and genetic mutations.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eIn summary, we demonstrated that SIGMAR1 knockdown affects key cellular processes, including mitochondrial function, calcium homeostasis, and clonogenic growth. Our findings suggest that SIGMAR1 contributes to OC pathogenesis by influencing mitochondrial calcium dynamics and decrease cell clonogenic growth. However, further investigation into the mechanisms underlying SIGMAR1's role in OC and its therapeutic implications is crucial for enhancing our understanding and developing effective treatment strategies for this challenging disease.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConsent for Publication:\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eConflicts of Interest:\u003c/h2\u003e\n\u003cp\u003eAll authors declare that they had no conflict of interest that could be perceived to impair the impartiality of the reported research.\u003c/p\u003e\n\u003ch2\u003eEthics approval and consent to participate:\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eThe study was supported by public Brazilian grants from the S\u0026atilde;o Paulo State Research Foundation (FAPESP), Grant numbers: 2016/19103-2, 2021/03732-9, 2022/07821-9.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eAll authors had full access to all data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: P.S.C designed, conducted, interpreted all experiments, drafted, and critically read the manuscript. C.S.B.G and H.I.S , provided laboratory assistance and critically revised the manuscript. W.A.Y and B.B helped discuss the results, edited the manuscript, and provided critical comments. A.M.L was responsible for the supervision, helped with concept and design, provided critical comments, edited, and revised the text for important intellectual content. All authors gave their final approval and agreed to be accountable for all aspects of the work.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe are grateful to Dr. J. Silvio Gutkind (UC San Diego, CA, USA) who kindly provided the NOK-SI cell line for the study.\u003c/p\u003e\n\u003ch2\u003eData availability statement:\u003c/h2\u003e\n\u003cp\u003eThe data presented in this study are available in this article. Additionally, other items that support the results of the study will be made available upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cdiv class=\"Heading\"\u003e\u003cb\u003eReferences\u003c/b\u003e:\u003c/div\u003e \u003cli\u003e\u003cspan\u003eBray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A (2024) Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEskander A, Dziegielewski PT, Patel MR, Jethwa AR, Pai PS, Silver NL, Sajisevi M, Sanabria A, Doweck I, Khariwala SS (2024) St John M. Oral Cavity Cancer Surgical and Nodal Management: A Review From the American Head and Neck Society. JAMA Otolaryngol Head Neck Surg 150:172\u0026ndash;178\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChow LQM (2020) Head and Neck Cancer. 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Cell Calcium 70:3\u0026ndash;15\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSopanaporn J, Suksawatamnuay S, Sardikin A, Lengwittaya R, Chavasiri W, Miyakawa T, Yompakdee C (2020) Pinostrobin suppresses the Ca2+-signal-dependent growth arrest in yeast by inhibiting the Swe1-mediated G2 cell-cycle regulation. FEMS Yeast Res ;20\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTagashira H, Bhuiyan MS, Shinoda Y, Kawahata I, Numata T, Fukunaga K (2023) Sigma-1 receptor is involved in modification of ER-mitochondria proximity and Ca. J Pharmacol Sci 151:128\u0026ndash;133\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSilvestri R, Nicol\u0026igrave; V, Gangadharannambiar P, Crea F, Bootman MD (2023) Calcium signalling pathways in prostate cancer initiation and progression. Nat Rev Urol 20:524\u0026ndash;543\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"molecular-biology-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mole","sideBox":"Learn more about [Molecular Biology Reports](https://www.springer.com/journal/11033)","snPcode":"11033","submissionUrl":"https://submission.nature.com/new-submission/11033/3","title":"Molecular Biology Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Oral cancer, SIGMAR1, mitochondrial Ca2+ signaling, therapeutic strategy","lastPublishedDoi":"10.21203/rs.3.rs-5333239/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5333239/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOral cancer is the most common malignancy of the oral cavity and facial region, affecting the mucosal and epithelial surfaces in the mouth and lips. Unfortunately, OC is often associated with a high mortality rate and limited treatment options for patients. \u0026nbsp;Herein, we used \u003cem\u003ein silico\u003c/em\u003e analysis and \u003cem\u003ein vitro\u003c/em\u003e assays to investigate the impact of the Sigma-1 receptor (SIGMAR1) in OC progression by evaluating mitochondrial function, calcium signaling and clonogenic growth. First, the data from the TCGA pan-cancer analysis revealed that SIGMAR1 was overexpressed in OC versus healthy tissue and related to a worse survival rate. Furthermore, we also demonstrated that SIGMAR1 silencing increased mitochondrial membrane potential, inhibited Ca\u003csup\u003e2+\u003c/sup\u003e influx and significantly decreased clonogenic growth of OC cells. \u0026nbsp;Based on these findings, we suggest that SIGMAR1 may influence mitochondrial membrane potential and energy production by modulating Ca\u003csup\u003e2+\u003c/sup\u003e uptake, which is critically important to cellular survival. In addition, SIGMAR1 knockdown may offer a potential strategy to be further explored as treatment for \u0026nbsp;OC.\u003c/p\u003e","manuscriptTitle":"Suppression of SIGMAR1 hinders oral cancer cell growth via modulation of mitochondrial Ca2+ dynamics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-15 12:01:49","doi":"10.21203/rs.3.rs-5333239/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-03T11:02:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-30T22:49:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-26T21:02:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-26T17:14:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"258657525388547631415428343222245151298","date":"2024-11-16T08:51:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"295485426677101067867359727776655200010","date":"2024-11-13T14:18:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"292101831430968920514038273942406738705","date":"2024-11-11T14:54:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"326342612196959273179976876962932898648","date":"2024-11-11T13:17:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-28T10:15:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-26T04:24:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-26T04:24:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"Molecular Biology Reports","date":"2024-10-25T14:48:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"molecular-biology-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mole","sideBox":"Learn more about [Molecular Biology Reports](https://www.springer.com/journal/11033)","snPcode":"11033","submissionUrl":"https://submission.nature.com/new-submission/11033/3","title":"Molecular Biology Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"b138a0d9-8400-4d04-a80f-cc06aedab619","owner":[],"postedDate":"November 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-17T16:07:35+00:00","versionOfRecord":{"articleIdentity":"rs-5333239","link":"https://doi.org/10.1007/s11033-025-10336-2","journal":{"identity":"molecular-biology-reports","isVorOnly":false,"title":"Molecular Biology Reports"},"publishedOn":"2025-02-11 15:58:00","publishedOnDateReadable":"February 11th, 2025"},"versionCreatedAt":"2024-11-15 12:01:49","video":"","vorDoi":"10.1007/s11033-025-10336-2","vorDoiUrl":"https://doi.org/10.1007/s11033-025-10336-2","workflowStages":[]},"version":"v1","identity":"rs-5333239","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5333239","identity":"rs-5333239","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}