Hypoxia-Induced MIF Induces Dysregulation of Lipid Metabolism in Laryngocarcinoma Through IL-6/JAK-STAT Pathway

Hypoxia-Induced MIF Induces Dysregulation of Lipid Metabolism in Laryngocarcinoma Through IL-6/JAK-STAT Pathway | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Hypoxia-Induced MIF Induces Dysregulation of Lipid Metabolism in Laryngocarcinoma Through IL-6/JAK-STAT Pathway Minlan Yang, Sa Wu, Weisong Cai, Xiaoping Ming, Yuhao Zhou, Xiong Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1439230/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose Hypoxia is a common feature of laryngocarcinoma. Alteration in lipid metabolism in hypoxic microenvironment is an important metabolic rewiring phenomenon for malignant cells to maintain their rapid proliferation, which makes most cancers, including laryngocarcinoma, hard to cure. However, the mechanism of lipid metabolism of laryngocarcinoma involved is still unclear. This study aimed to make clear the changes in lipid metabolism of laryngocarcinoma cell under hypoxic condition and explore the relative mechanism. Methods Hep2 cells were placed in a normoxic or hypoxic environment (5% CO2, 94% N2 and 1% O2) at 37℃ for 24 h. After exposed to hypoxia, lip metabolic indices including TG and NEFA were tested. The mechanism involved in lip metabolism regulation was explored by RNA seq and bioinformatic analysis. MIF inhibitor ISO-1 and JAK inhibitor XL019 were used to verify the mechanism. Finally, tumour xenograft model was applied has further verified these results in vivo. Results Hypoxia increased the TG and NEFA levels of Hep2 cells. Three genes, intersection of hypoxia gene sets and fatty gene sets, including MIF, ENO2, and LDHA were screened and verified by qPCR. MIF levels were elevated when exposed to hypoxia. Through GSEA and RNA-seq analysis, JAK/STAT pathway was screened. Hypoxia increased MIF and activated IL-6/JAK/STAT pathway. MIF inhibitor ISO-1 reversed TG levels, IL-6 levels, and reversed the expression pattern of screened genes in JAK/STAT pathway. Tumour xenograft model has further verified these results. Conclusion Hypoxia induced reprogramming of lipid metabolism in laryngocarcinoma cells through MIF/IL-6/JAK-STAT pathway. This study revealed one mechanism that allows laryngocarcinoma cells adapt to hypoxic tumor microenvironment. Therefore, a drug targeting MIF/IL-6/JAK-STAT pathway might be a promising therapeutic option for the treatment of laryngeal cancer. hypoxia MIF lipid metabolism IL-6/JAK-STAT pathway Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Hypoxia is a common phenomenon in the tumor microenvironment. In the process of tumor progression, due to the rapid proliferation of tumor cells, the vascular network cannot be established quickly and the new blood vessels are structurally abnormal, resulting in a decrease in oxygen content in the microenvironment, lack of nutrients and accumulation of acidic substances. In the hypoxic microenvironment, tumor cells can improve their adaptability by changing ways of metabolism, inhibiting the anti-tumor effects of immune cells, prone to invasion, metastasis, and drug-resistance. Therefore, the hypoxic microenvironment increases the difficulty of tumor treatment. Lipids, proteins, and nucleic acids are important components of the biological membranes and structural units of cells. Lipids are used for energy storage and metabolism and play important signaling molecular roles in a variety of cellular activities. The regulation of lipid metabolism, such as lipid uptake, synthesis, and hydrolysis, is essential for maintaining cell homeostasis. In the process of tumor progression, the availability of nutrients in the tumor microenvironment is constantly changing, tumor cells undergo lipid metabolism to maintain rapid proliferation, survival, migration, invasion, and metastasis. To adapt to the hypoxic microenvironment, the metabolism of tumors will also undergo corresponding changes. Hypoxia enhances lipogenesis by HIF-dependent modulation of proteins involved in fatty acid (FA) uptake, synthesis, storage and usage, enhancing cancer progression and hypoxia-induced chemoresistance[ 1 – 3 ]. Hypoxia-induced alteration of lipid metabolism promotes cancer malignant progression has been explored in various cancers. In prostate cancer, hypoxic cells accumulate a higher amount of lipids and decreased fatty acid oxidation, protecting cancer cells from oxidative and endoplasmic reticulum stress, and playing important roles in fueling cell proliferation[ 4 ]. In clear cell renal cell carcinoma (ccRCC), HIF1 and HIF2 repressed target gene CPT1A, thus reducing fatty acid transport into the mitochondria, and forcing fatty acids to lipid droplets for storage, which is essential for ccRCC tumorigenesis[ 5 ]. In a hypoxic microenvironment, HIF-2α upregulation promotes steatotic hepatocellular carcinoma progression by activating lipid synthesis via the PI3K-AKT-mTOR pathway[ 6 ]. Inhibition of lipid storage decreased the survival of cells subjected to hypoxia-reoxygenation and strongly impaired tumorigenesis in multiple cancers[ 7 ]. As laryngeal cancer is a common disease in otorhinolaryngology, and with increasing incidence rate in recent years. We aim to explore the role of hypoxia in the lipid metabolism in laryngeal cancer cells in this study. Methods And Materials 1. Cell culture A human laryngeal squamous cancer cell line, Hep2, was purchased from Medical Science Research Center, Zhongnan Hospital of Wuhan University, and cultured in Dulbecco’s modified Eagle’s medium supplemented with 10% fetal bovine serum, 100U/ml penicillin and 100µg/ml streptomycin. Cells were maintained at 37℃ in a humidified incubator with a mixture of 95% air (20% O 2 ) and 5% CO 2 . 1%O 2, 94%N2 and 5%CO 2 was chosen for hypoxia experiment. MIF inhibitor ISO-1 (SML0472) was purchased from Sigma-Aldrich, and JAK inhibitor XL019 was purchased from Beyotime Biotechnology. 2. Western blotting For Western blotting, cells were lysed with RIPA lysis buffer kit (Beyotime, China), supernatants were collected after spin and total proteins were measured using the BCA protein quantification kit (Beyotime, China). Total protein samples were separated by 10% sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). Then, the samples were transferred onto 0.22µm PVDF membranes. After blocking with 5% fat-free milk for 1 hour at room temperature, the membranes were incubated with primary antibodies overnight at 4℃. Following three washes with TBST buffer, the membranes were incubated with secondary goat anti-rabbit antibodies conjugated with HRP for 1 hour at room temperature. Signals were visualized using the enhanced chemiluminescence kit (Beyotime, China) and detected by the Imaging system (Baygene Biotech, China). Integrated relative densities of individual bands were quantified using Image J (National Institutes of Health, Bethesda, MD). 3. Quantitative real-time PCR Total RNA was extracted following the manufacturer's protocol with TRIzol reagent (Invitrogen, CA), dissolved in RNA-free H 2 O and stored at -80°C. cDNA synthesis was performed from each 1µg RNA sample using the Reverse Transcriptase Kit (Thermo, USA). Then qRT-PCR was performed on a CFX96 Connect (Bio-Rad, CA) using a SYBR Green PCR kit (Vazyme Biotech, China). Expression data were calculated using the 2 −ΔΔCt method and normalized by taking GAPDH as an internal reference to control the relative expression levels. Primer sequences were listed in Table 1. 4. ELISA assay MIF and IL-6 concentrations were detected by enzyme-linked immunosorbent assay (ELISA) kits according to the manufacturer’s protocol. Quantitative IL-6 ELISA assay kit was purchased from QuantiCyto (China), Quantitative MIF ELISA assay kit was purchased from Elabscience (USA), and TG, NEFA levels were estimated by assay kits (Nanjing Jiancheng Bioengineering Institute, China). All were used according to the manufacturers’ instructions. All samples were measured in triplicate and average values were determined. 5. Bioinformatics analysis Hypoxia gene sets and fatty gene sets were downloaded from Gene Set Enrichment Analysis(GSEA, http://www.gsea-msigdb.org/gsea/index.jsp ) and Venn diagrams were used to analyze the intersection of the two gene sets. Gene expression profiles of larynx were downloaded from TCGA ( https://portal.gdc.cancer.gov/ ). Gene Set Enrichment Analysis (GSEA) was performed using GSEA software 4.0.3(USA). 6. RNA-seq Transcriptome sequencing and analysis were performed by the BGI Company ( http://bgitechsolutions.com ). Total RNA was extracted following the manufacturer's protocol with TRIzol reagent (Invitrogen, CA), dissolved in RNA-free H 2 O and stored at -80°C. Total RNA was processed by mRNA enrichment: The mRNA with polyA tail was enriched by magnetic beads with OligodT. The RNA obtained was segmented by interrupting buffer, and the random N6 primers were reversely transcribed, and then the cDNA two-strand was synthesized to form double-stranded DNA. The synthetic double-stranded DNA ends are flattened and phosphorylated at the 5' end to form A sticky end protruding an "A" at the 3' end, followed by A bubbling-like connector protruding A "T" at the 3' end. The ligands were amplified by PCR using specific primers. The PCR product was thermally denatured into single strand, and then the single strand DNA was cycled with a bridge primer to obtain a single strand circular DNA library. The constructed library was inspected and sequenced after qualified. The resulting data are referred to as RAW reads or RAW data, and the RAW reads are then subjected to quality control (QC) to determine whether the sequenced data are suitable for subsequent analysis. After quality control, the filtered clean reads were compared to the reference sequence. After alignment, the distribution of alignment rate and reads on the reference sequence was counted to determine whether alignment results passed the second QC of alignment. If passed, gene quantitative analysis was carried out and differential gene expression among screened samples will be conducted. 7. Immunohistochemistry staining Tissue slides were deparaffinized in xylene and rehydrated in alcohol. Then, antigen retrieval was performed with 0.1 M sodium citrate buffer. Subsequently, the sections were blocked by performing IHC kit(Maixin China) and probed with primary antibodies for 1 h at room temperature. Slides were incubated with poly-HRP secondary antibodies by performing IHC kit, after which sections were counterstained with haematoxylin to visualize nuclei. Images were analyzed by using Image J v1.8.0(National Institutes of Health, USA). 8. Animal experiment All mice were maintained at Zhongnan Hospital of Wuhan University and all animal experiments were performed in accordance with Zhongnan Hospital animal ethics committee(Wuhan, China). Male BABL/c nude mice (4 weeks old) were purchased from Gempharmatech (Zhejiang, China). Hep2 cells were resuspended at 2×10 7 cells/mL using saline, and each mouse was subcutaneously injected 200 µL into the right anterior flank. After 8 days, the mice were randomly divided into treatment group and control group(5 mice per group). The treatment group was treated with ISO-1(2.5 mg/kg, intraperitoneally, every day) and the control group was treated with saline(equal volume per weight, intraperitoneally, every day). Tumor volume was measured using a caliper every other day, and volumes were calculated using the standard formula: V = 0.5*length*width 2 . Finally, mice were euthanized, and tumors were removed, photographed, weighed and collected for ELISA and immunohistochemistry. 9. Statistical analysis All data were represented as means ± standard deviations (SD). All differences between two independent groups were analyzed using Students’ t test. SPSS 20.0 software (IBM Corporation, USA) was used for statistical analysis. A P -value < 0.05 was considered statistically significant. Results Hypoxia affects lipid metabolism in Hep2 cells Hypoxia inducible factor 1 subunit alpha (HIF1A), which is an adaptive factor in the hypoxic environment, was found higher expressed when Hep2 cells exposed hypoxic environment as 1% O 2 (Fig. 1 A). To make sure whether hypoxia affects HNSCC lipid metabolism, Triglycerides (TG), which is a constituent of lipids, were detected. We found that hypoxia evidently increased the TG level of Hep2 cells(Fig. 1 B). Besides, non-esterified free fatty acids (NEFA) are the major component of triglycerides, we also found that hypoxia increased NEFA level in Hep2 cells(Fig. 1 C). Furthermore, we found that the expression pattern of some lipid metabolism related genes was changed, the expressions of PPARA, PPARG, SREBF1, FASN, PPARD were downregulated, and LPIN2 was upregulated when exposed to hypoxia(Fig. 1 D). According to these findings, it suggested that hypoxia may make a role in regulating lipid metabolism in HNSCC cells. MIF may be a key factor in hypoxia regulating lipid metabolism As hypoxia is a common feature of solid tumors, cancer cells confront the compound challenges of high growth rates and limited and unreliable supply of O 2 , therefore cancer cells change the pattern of metabolism to adapt to hyperproliferation. To explore whether lipid metabolism is involved when laryngeal cancer exposed to hypoxia microenvironment, we analyzed the hypoxia gene sets and fatty gene sets, three genes such as Lactate dehydrogenase A (LDHA), enolase 2 (ENO2) and macrophage migration inhibitory factor (MIF) may be involved in lipid metabolism in laryngeal cancer(Fig. 2 A). In consistent with the intersection of the hypoxia gene sets and fatty gene sets by bioinformatics analysis, hypoxia significantly upregulated the expression of LDHA, ENO2 and MIF(Fig. 2 B). As MIF is a classical pro-inflammatory cytokine that is secreted by immune cells and certain other cell types, we found that the protein level of MIF is increased when exposed to hypoxia. Since MIF is also a key factor in lipid metabolism disturbance, we hypothesized that MIF signaling may play a great role in hypoxia-inducing lipid metabolic disorder. To verify whether MIF is the main factor in hypoxia affecting lipid metabolism, ISO-1, a MIF antagonist was used. We found that 25µM ISO-1 significantly inhibited the protein level of MIF, and in the condition of hypoxic environment(Fig. 2 C, 2 D), ISO-1 evidently decreased the TG level of Hep2 cells (P 0.05)(Fig. 2 F). To further verify the role of MIF in lipid metabolism, we found that ISO-1 reversed the expression of lipid metabolism related genes(Fig. 2 G). JAK/STAT signaling is involved in MIF regulating pathways in laryngeal cancer GSEA analysis was used to screen the pathways which are involved in MIF regulating pathways in laryngeal cancer(Gene sets enriched in phenotype l (251 samples)), we found that the top 10 pathways were JAK STAT SIGNALING PATHWAY, ADHERENS JUNCTION, ARRHYTHMOGENIC RIGHT VENTRICULAR CARDIOMYOPATHY ARVC, ECM RECEPTOR INTERACTION, HUNTINGTONS DISEASE, ALZHEIMERS DISEASE, OXIDATIVE PHOSPHORYLATION, PARKINSONS DISEASE, GLUTATHIONE METABOLISM and SPLICEOSOME(Table.1). MIF was an upstream modulator of IL-6 and the IL-6/JAK/STAT pathway has a key role in the growth and development of many human cancers. Thence we hypothesized that hypoxia inducing MIF regulating lipid metabolism may through activating IL-6/JAK/STAT signaling(Fig. 3 A). 14 genes were found to be consistent by the intersection of JAK/STAT pathway gene sets and RNA-seq(Fig. 3 B). RT-qPCR was used to verify and the gene expression profile is basically consistent with the analysis(Fig. 3 C), confirming that hypoxia activated JAK/STAT signaling pathway. Hypoxia induces MIF regulating lipid metabolism through activating IL-6/JAK/STAT signaling When exposed to hypoxia, the mRNA and protein levels of IL-6 were increased(Fig. 4 A, 4 B). ISO-1 significantly reversed hypoxia inducing IL-6 upregulation(Fig. 4 C, 4 D). RT-qPCR assay was applied to test the mRNA expression of JAK/STAT pathway genes, it revealed that ISO-1 reversed the expression pattern of JAK/STAT pathway genes profile, suggesting hypoxia activating IL-6/JAK/STAT pathway via MIF(Fig. 4 E). To further verify that MIF regulating lipid metabolism through activating IL-6/JAK/STAT pathway, JAK inhibitor XL019 was used, we found that XL019 significantly decreased the TG level of Hep2 cells when exposed to hypoxia(Fig. 4 F), it confirmed that inhibition of JAK signaling reversed hypoxia inducing abnormal lipid metabolism. MIF antagonist ISO1 inhibits the tumorigenicity of Hep2 cells in vivo To evaluate whether MIF plays a role in tumorigenicity in vivo, we applied ISO1, a MIF antagonist, to tumor-bearing mice. ISO1 significantly inhabited the tumor growth in vivo(Fig. 5 A). Tumor weight(Fig. 5 B) obviously decreased in mice injected with ISO1 compared with control mice. Furthermore, the positive rate of Ki67, which reflects the proliferation of cells, was obviously lower in the ISO1 treatment group(Fig. 5 C). In inconsistent with the results of cell experiment, the concentration of serum IL6(Fig. 5 D) and serum TG(Fig. 5 E) was decreased with ISO1 treatment. To explore the mechanism of cancer cells adapting to hypoxic microenvironment, we conducted RT-qPCR assay to test the mRNA expression of JAK/STAT pathway genes of tumor xenograft tissues. The results were basically accordance with the cellular data(Fig. 5 F). In summary, all these results suggest that hypoxia activated IL-6/JAK/STAT pathway via MIF. Discussion Lipids, proteins and nucleic acids are important components of the biological membranes and structure of cells. In addition, lipids are also used for energy storage and metabolism and play important signaling molecular roles in a variety of cellular activities. The regulation of lipid metabolism, such as lipid uptake, synthesis, and hydrolysis, is essential for maintaining cell homeostasis. In the process of tumor progression, the availability of nutrients in the tumor microenvironment is constantly changing, tumor cells alter lipid metabolism to maintain rapid proliferation, survival, metastasis and chemoresistance. Under hypoxic conditions, cancer cells increase the utilization of extracellular lipids to meet the demand for bioenergy and biosynthesis and to maintain membrane homeostasis. Fatty acid metabolism maintains tumorigenesis, progression and treatment resistance by enhancing lipid synthesis, storage and catabolism. In addition, tumor cells exhibit plasticity in fatty acid metabolism and respond to extraneous and systemic metabolic signals (such as obesity and tumor therapy) to promote aggressiveness, treatment and resistance to the development of related diseases[ 8 ]. In our study, we found that hypoxia increased TG and NEFA levels in Hep2 cells, and then we screened the fat acid metabolism related genes in hypoxia gene sets of laryngeal cancer. MIF, ENO2 and LDHA were screened as related to lipid metabolism when laryngeal cancer cells exposed to hypoxia, which is consistent with the RNA-seq analysis of Hep2 cells that exposed to hypoxia. MIF is over-expressed and secreted in various cancer cells in particular in response to hypoxia. As a multifunctional inflammatory cytokine, MIF is related to tumorigenesis, angiogenesis and metastasis of many cancer phenotypes. MIF can potentially promote tumorigenesis by inhibiting the classic tumor suppressor gene p53, regulating cell cycle arrest and apoptosis in response to DNA damage[ 9 ]. Besides, inhibition of MIF can reduce the formation of the pre-metastasis microenvironment in the liver and the metastasis of cancer cells[ 10 ]. In recent years, MIF was reported associated with lipid metabolism in multiple diseases. Changes in expression levels of MIF have an important impact on metabolism and immune regulation of adipose cells. MIF deficiency aggravates the effects of energy-rich fructose diet on hepatic lipid accumulation in the mouse liver[ 11 ]. MIF upregulation reduced lipolysis and increased lipogenic pathways in adipose tissue[ 12 ]. MIF deficiency reduces chronic inflammation in white adipose tissue[ 13 ]. We verified that hypoxia inducing increased TG and NEFA levels via upregulating of MIF by antagonist, ISO-1. And ISO-1 reversed the expression pattern of lipid metabolism related genes, such as PPARA, PPARG, SREBF1, FASN, LPIN2. Through subcutaneous xenograft model, we found that tumors was significantly growth-restricted with ISO-1 treatment. Consistently, the serum IL6 and TG levels of mice showed the same trend. However, there were no statistically significant differences possibly due to large individual variations. More mice are needed for a reliable conclusion. Besides the key role of MIF on the inflammatory cascade and its ability to counteract glucocorticoid-induced anti-inflammatory responses, MIF also participates in regulating malignant phenotypes of various cancers through activating multiple signaling pathways. MIF expression is abnormally increased and supports the proliferation, migration and invasion of breast cancer, gastric cancer, pancreatic cancer and lung cancer cells[ 14 – 17 ]. MIF acts as an autocrine growth factor involved in cell cycle in pancreatic cancer cells[ 18 ]. In bladder cancer cells, activation of CXCL2/MIF-CXCR2 signaling induced MDSC accumulation and expansion in the bladder cancer microenvironment[ 19 ]. MIF/CXCR7/AKT pathway drives growth and metastasis in castration-resistant prostate cancer cells[ 20 ]. To further analyze the molecular mechanism of MIF in regulating lipid metabolism, we screened the related pathway through GSEA analysis, and we found the top one pathway is JAK/STAT pathway. Through the intersection of JAK/STAT pathway gene sets and RNA-seq, we screened that 14 genes showed the same expression patterns, and RT-qPCR results basically verified it in vitro and in vivo. Due to large individual variations of each mouse, a part of genes did not show a siganificant difference even though the trend of gene expression in vivo was consistent with the results in vitro. As MIF was an upstream modulator of IL-6, and IL-6 is the classical upstream activator of JAK/STAT pathway, IL-6 binds to its receptor IL-6R, and induces homodimerization and formation of a high affinity receptor complex, activating MAPK, PI3K/AKT pathways, to regulate growth, differentiation, survival and chemoresistance of cancer cells[ 21 – 23 ]. JAK/STAT signaling pathway is continuously activated and overexpressed in a variety of tumor cells, the continuously activated JAK/STAT pathway in the tumor microenvironment can inhibit the anti-tumor immune response of immune cells, IL-6/JAK/STAT signal has become a hot signal target for tumor therapy[ 24 ]. MIF promotes the secretion of the inflammatory factor IL-6 in the tumor hypoxic microenvironment, and promotes the malignant progression of laryngeal cancer and changes in lipid metabolism, suggesting that MIF/IL-6/JAK/STAT pathway is expected to provide a new approach for the treatment of laryngeal cancer. Abbreviations HNSCC head and neck squamous cell carcinoma ELISA enzyme-linked immunosorbent assay GSEA gene set enrichment analysis IHC immunohistochemistry NEFA non-esterified free fatty acids FA fatty acid TG triglycerides HIF1A hypoxia inducible factor 1 subunit alpha MIF macrophage migration inhibitory factor LDHA lactate dehydrogenase A ENO2 enolase 2 Declarations Ethics approval The animal study was reviewed and approved by the Ethics Committee of Zhongnan Hospital of Wuhan University. Consent for publication Not applicable Availability of data and materials The following information was supplied regarding data availability: The gene expression profiles containing the clinical follow-up information is available at TCGA website(https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga). The other data used to support the findings of this study are available from the corresponding author upon request. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Funding This work was partly supported by the National Natural Science Foundation of China (NO. 81902599). Author Contributions Minlan Yang: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data Curation, Writing-Original Draft. Sa Wu: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data Curation, Writing-Original Draft. Weisong Cai: Methodology, Validation, Software, Formal analysis, Investigation, Data Curation, Writing-Original Draft. Xiaoping Ming: Resources, Data Curation. Yuhao Zhou: Data Curation, Visualization. Xiong Chen: Writing- Review & Editing, Supervision. All authors have participated sufficiently in the study and approved the final version Data Availability The following information was supplied regarding data availability: The gene expression profiles containing the clinical follow-up information is available at TCGA website(https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga). The other data used to support the findings of this study are available from the corresponding author upon request. Acknowledgements Not applicable References C. Corbet, O. Feron, Emerging roles of lipid metabolism in cancer progression, Curr Opin Clin Nutr Metab Care, 20 (2017) 254–260, https://doi.org/10.1097/MCO.0000000000000381 . X. Luo, C. Cheng, Z. Tan, N. Li, M. Tang, L. 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Grandis, Targeting the IL-6/JAK/STAT3 signalling axis in cancer, Nat Rev Clin Oncol, 15 (2018) 234–248, https://doi.org/10.1038/nrclinonc.2018.8 . P. Sansone, J. Bromberg, Targeting the interleukin-6/Jak/stat pathway in human malignancies, J Clin Oncol, 30 (2012) 1005–14, https://doi.org/10.1200/JCO.2010.31.8907 . J. Lokau, V. Schoeder, J. Haybaeck, C. Garbers, Jak-Stat Signaling Induced by Interleukin-6 Family Cytokines in Hepatocellular Carcinoma, Cancers (Basel), 11 (2019), https://doi.org/10.3390/cancers11111704 . C.S. Roxburgh, D.C. McMillan, Therapeutics targeting innate immune/inflammatory responses through the interleukin-6/JAK/STAT signal transduction pathway in patients with cancer, Transl Res, 167 (2016) 61 – 6, https://doi.org/10.1016/j.trsl.2015.08.013 . Tables Table.1 GSEA analysis of MIF in laryngeal carcinoma Description setSize enrichScore NES pvalue KEGG_JAK_STAT_SIGNALING_PATHWAY 155 -0.59 -2.19 0.003 KEGG_ADHERENS_JUNCTION 73 -0.65 -2.11 0.005 KEGG_ARRHYTHMOGENIC_RIGHT_VENTRICULAR_CARDIOMYOPATHY_ARVC 74 -0.65 -2.08 0.007 KEGG_ECM_RECEPTOR_INTERACTION 84 -0.71 -2.03 0.011 KEGG_HUNTINGTONS_DISEASE 180 0.68 2.31 0 KEGG_ALZHEIMERS_DISEASE 165 0.63 2.23 0 KEGG_OXIDATIVE_PHOSPHORYLATION 131 0.78 2.21 0 KEGG_PARKINSONS_DISEASE 128 0.75 2.21 0 KEGG_GLUTATHIONE_METABOLISM 49 0.68 2.11 0.003 KEGG_SPLICEOSOME 127 0.7 2.1 0.003 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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-1439230","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":90567356,"identity":"e135b626-865e-4064-8381-549757cafcd2","order_by":0,"name":"Minlan Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYNCCAhsGAxDNQ7wWgzTStRwmQYvB8bOHX90wOJ+4XSKB8cHbNgZ5c4JazuSlWecY3E7cOSOB2XBuG4PhzgZCWg7kmBkDteRuuJHAJs3bxpBgcICQlvNvQFrOgbSw/yZOy40c48c5BgfAtjATpUXyxhsz5hyD5PoNZx42S845J2G4gZAWvvM5xp9zKuyMDY4nH/zwpsxGnqAtCgcY2CQgTMYGICFBQD0QyDcwMH8grGwUjIJRMApGNAAASpBDyhlHrpEAAAAASUVORK5CYII=","orcid":"","institution":"Zhongnan hospital of Wuhan University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Minlan","middleName":"","lastName":"Yang","suffix":""},{"id":90567357,"identity":"103522f2-6544-4008-a7e0-369e7b55d3a4","order_by":1,"name":"Sa Wu","email":"","orcid":"","institution":"Zhongnan hospital of Wuhan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sa","middleName":"","lastName":"Wu","suffix":""},{"id":90567359,"identity":"be39cbff-133c-481c-a294-314532ce9175","order_by":2,"name":"Weisong Cai","email":"","orcid":"","institution":"Zhongnan hospital of Wuhan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Weisong","middleName":"","lastName":"Cai","suffix":""},{"id":90567361,"identity":"9367068c-95c5-4f24-95eb-527e658f69a3","order_by":3,"name":"Xiaoping Ming","email":"","orcid":"","institution":"Zhongnan hospital of Wuhan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaoping","middleName":"","lastName":"Ming","suffix":""},{"id":90567363,"identity":"642cebb6-86a7-40d6-aa44-1ab4c95e2121","order_by":4,"name":"Yuhao Zhou","email":"","orcid":"","institution":"Zhongnan hospital of Wuhan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuhao","middleName":"","lastName":"Zhou","suffix":""},{"id":90567364,"identity":"ea2e6a66-cecc-4f46-886f-4cdf8f1f6ce4","order_by":5,"name":"Xiong Chen","email":"","orcid":"","institution":"Zhongnan hospital of Wuhan University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiong","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2022-03-10 16:29:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1439230/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1439230/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":19308426,"identity":"d1b86c0a-f218-41c4-a785-edefdfdbd813","added_by":"auto","created_at":"2022-03-16 20:55:00","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1493026,"visible":true,"origin":"","legend":"\u003cp\u003eHypoxia affects lipid metabolism in Hep2 cells. Hep2 cells were treated under hypoxia environment 24h. (A) Protein level of HIF1A were assessed by western blot. (B) TG concentration was assessed by TG assay. (C) NEFA concentration was assessed by NEFA assay. (D) Expressions of lipid metabolism related genes were screened out by. The data are presented as mean ± SD. *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001.\u0026nbsp;\u003c/p\u003e","description":"","filename":"fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1439230/v1/a624bfe14e5975bf876b21e4.jpg"},{"id":19308429,"identity":"9cd1722b-0bbe-40c5-a059-db258a50d430","added_by":"auto","created_at":"2022-03-16 20:55:01","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2755095,"visible":true,"origin":"","legend":"\u003cp\u003eMIF may be a key factor in hypoxia regulating lipid metabolism. (A) Venn diagram showed the intersection of hypoxia gene sets and fatty gene sets. (B) The mRNA expression of MIF, ENO2 and LDHA were verified by qRT-PCR. (C) Protein level of MIF was assessed by ELISA assay. Hep2 cells were treated with 25μM ISO-1. Then MIF protein level(C), TG(D) and NEFA(E) concentration was assessed. The data are presented as mean ± SD. *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001.\u0026nbsp;\u003c/p\u003e","description":"","filename":"fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1439230/v1/377a049ce862d3981451f0d4.jpg"},{"id":19308485,"identity":"5348540c-e4c7-4dd4-9512-83a6f59215a0","added_by":"auto","created_at":"2022-03-16 20:58:00","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1641035,"visible":true,"origin":"","legend":"\u003cp\u003eJAK/STAT signaling is involved in MIF regulating pathways in laryngeal cance. (A) GSEA analysis showed JAK/STAT signaling is involved in MIF regulating pathways in laryngeal cance. (B) Venn diagram showed the intersection of JAK/STAT gene sets and differently expressed genes in RNA seq. (C) qRT-PCR showed the intersection gene expression is basically consistent the analysis under hypoxia. The data are presented as mean ± SD. *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001; ****p \u0026lt; 0.0001.\u003c/p\u003e","description":"","filename":"fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1439230/v1/50c458d21f82db6edcc5d0f9.jpg"},{"id":19308427,"identity":"316d4432-1765-4726-bf74-fb37071e7c01","added_by":"auto","created_at":"2022-03-16 20:55:00","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2256961,"visible":true,"origin":"","legend":"\u003cp\u003eHypoxia induces MIF regulating lipid metabolism through activating IL-6/JAK/STAT signaling. Hep2 cells were treated with 25μM ISO-1 under hypoxia. Then the mRNA(A) and protein level(B) of IL-6 were assessed by qRT-PCR and western blot. (C)The intersection gene expressions of JAK/STAT gene sets and differently expressed genes in RNA seq were verified. (D) TG concentration of Hep2 cells treated with XL019 or solvent under hypoxia. The data are presented as mean ± SD. *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001.\u0026nbsp;\u003c/p\u003e","description":"","filename":"fig.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1439230/v1/08b042bc72b8478427593ad6.jpg"},{"id":19308430,"identity":"4d5f0cf0-d4d3-41c9-a4c0-c906b783f5c0","added_by":"auto","created_at":"2022-03-16 20:55:01","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3151699,"visible":true,"origin":"","legend":"\u003cp\u003eMIF antagonist ISO1 inhibits the tumorigenicity of Hep2 cells in vivo. Four-week-old nude mice (five mice per group) were subcutaneously injected with the Hep2 cells (4 * 10\u003csup\u003e6\u003c/sup\u003e cells each mouse) and treated with ISO1 at day eight. (A) The\u0026nbsp;tumor\u0026nbsp;growth\u0026nbsp;curves\u0026nbsp;in vivo. (B) Picture of isolated tumors and tumor weight. (C) Images and statistic results of positive rate of Ki67. (D) Serum IL6 level and (E) serum TG level were assessed by ELISA assay. (F) qRT-PCR was applied to detect relative mRNA expression of JAK/STAT gene sets. The data are presented as mean ± SD. *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001.\u0026nbsp;\u003c/p\u003e","description":"","filename":"fig.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-1439230/v1/2d6dbb53caddc20f0cede832.jpg"},{"id":19308486,"identity":"e9603030-5664-4325-b5d7-c761ccea2715","added_by":"auto","created_at":"2022-03-16 20:58:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":736457,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1439230/v1/a7859644-0689-4a3c-bd72-1c5d5454ad9e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eHypoxia-Induced MIF Induces Dysregulation of Lipid Metabolism in Laryngocarcinoma Through IL-6/JAK-STAT Pathway\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHypoxia is a common phenomenon in the tumor microenvironment. In the process of tumor progression, due to the rapid proliferation of tumor cells, the vascular network cannot be established quickly and the new blood vessels are structurally abnormal, resulting in a decrease in oxygen content in the microenvironment, lack of nutrients and accumulation of acidic substances. In the hypoxic microenvironment, tumor cells can improve their adaptability by changing ways of metabolism, inhibiting the anti-tumor effects of immune cells, prone to invasion, metastasis, and drug-resistance. Therefore, the hypoxic microenvironment increases the difficulty of tumor treatment. Lipids, proteins, and nucleic acids are important components of the biological membranes and structural units of cells. Lipids are used for energy storage and metabolism and play important signaling molecular roles in a variety of cellular activities. The regulation of lipid metabolism, such as lipid uptake, synthesis, and hydrolysis, is essential for maintaining cell homeostasis. In the process of tumor progression, the availability of nutrients in the tumor microenvironment is constantly changing, tumor cells undergo lipid metabolism to maintain rapid proliferation, survival, migration, invasion, and metastasis. To adapt to the hypoxic microenvironment, the metabolism of tumors will also undergo corresponding changes. Hypoxia enhances lipogenesis by HIF-dependent modulation of proteins involved in fatty acid (FA) uptake, synthesis, storage and usage, enhancing cancer progression and hypoxia-induced chemoresistance[\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e]. Hypoxia-induced alteration of lipid metabolism promotes cancer malignant progression has been explored in various cancers. In prostate cancer, hypoxic cells accumulate a higher amount of lipids and decreased fatty acid oxidation, protecting cancer cells from oxidative and endoplasmic reticulum stress, and playing important roles in fueling cell proliferation[\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e]. In clear cell renal cell carcinoma (ccRCC), HIF1 and HIF2 repressed target gene CPT1A, thus reducing fatty acid transport into the mitochondria, and forcing fatty acids to lipid droplets for storage, which is essential for ccRCC tumorigenesis[\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e]. In a hypoxic microenvironment, HIF-2\u0026alpha; upregulation promotes steatotic hepatocellular carcinoma progression by activating lipid synthesis via the PI3K-AKT-mTOR pathway[\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e]. Inhibition of lipid storage decreased the survival of cells subjected to hypoxia-reoxygenation and strongly impaired tumorigenesis in multiple cancers[\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e]. As laryngeal cancer is a common disease in otorhinolaryngology, and with increasing incidence rate in recent years. We aim to explore the role of hypoxia in the lipid metabolism in laryngeal cancer cells in this study.\u003c/p\u003e"},{"header":"Methods And Materials","content":"\u003cp\u003e\u003cstrong\u003e1. Cell culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA human laryngeal squamous cancer cell line, Hep2, was purchased from Medical Science Research Center, Zhongnan Hospital of Wuhan University, and cultured in Dulbecco\u0026rsquo;s modified Eagle\u0026rsquo;s medium supplemented with 10% fetal bovine serum, 100U/ml penicillin and 100\u0026micro;g/ml streptomycin. Cells were maintained at 37℃ in a humidified incubator with a mixture of 95% air (20% O\u003csub\u003e2\u003c/sub\u003e) and 5% CO\u003csub\u003e2\u003c/sub\u003e. 1%O\u003csub\u003e2,\u003c/sub\u003e 94%N2 and 5%CO\u003csub\u003e2\u003c/sub\u003e was chosen for hypoxia experiment. MIF inhibitor ISO-1 (SML0472) was purchased from Sigma-Aldrich, and JAK inhibitor XL019 was purchased from Beyotime Biotechnology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. Western blotting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor Western blotting, cells were lysed with RIPA lysis buffer kit (Beyotime, China), supernatants were collected after spin and total proteins were measured using the BCA protein quantification kit (Beyotime, China). Total protein samples were separated by 10% sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). Then, the samples were transferred onto 0.22\u0026micro;m PVDF membranes. After blocking with 5% fat-free milk for 1 hour at room temperature, the membranes were incubated with primary antibodies overnight at 4℃. Following three washes with TBST buffer, the membranes were incubated with secondary goat anti-rabbit antibodies conjugated with HRP for 1 hour at room temperature. Signals were visualized using the enhanced chemiluminescence kit (Beyotime, China) and detected by the Imaging system (Baygene Biotech, China). Integrated relative densities of individual bands were quantified using Image J (National Institutes of Health, Bethesda, MD).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. Quantitative real-time PCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted following the manufacturer\u0026apos;s protocol with TRIzol reagent (Invitrogen, CA), dissolved in RNA-free H\u003csub\u003e2\u003c/sub\u003eO and stored at -80\u0026deg;C. cDNA synthesis was performed from each 1\u0026micro;g RNA sample using the Reverse Transcriptase Kit (Thermo, USA). Then qRT-PCR was performed on a CFX96 Connect (Bio-Rad, CA) using a SYBR Green PCR kit (Vazyme Biotech, China). Expression data were calculated using the 2\u003csup\u003e\u0026minus;\u0026Delta;\u0026Delta;Ct\u003c/sup\u003e method and normalized by taking GAPDH as an internal reference to control the relative expression levels. Primer sequences were listed in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. ELISA assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMIF and IL-6 concentrations were detected by enzyme-linked immunosorbent assay (ELISA) kits according to the manufacturer\u0026rsquo;s protocol. Quantitative IL-6 ELISA assay kit was purchased from QuantiCyto (China), Quantitative MIF ELISA assay kit was purchased from Elabscience (USA), and TG, NEFA levels were estimated by assay kits (Nanjing Jiancheng Bioengineering Institute, China). All were used according to the manufacturers\u0026rsquo; instructions. All samples were measured in triplicate and average values were determined.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5. Bioinformatics analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHypoxia gene sets and fatty gene sets were downloaded from Gene Set Enrichment Analysis(GSEA, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.gsea-msigdb.org/gsea/index.jsp\u003c/span\u003e\u003c/span\u003e) and Venn diagrams were used to analyze the intersection of the two gene sets. Gene expression profiles of larynx were downloaded from TCGA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://portal.gdc.cancer.gov/\u003c/span\u003e\u003c/span\u003e). Gene Set Enrichment Analysis (GSEA) was performed using GSEA software 4.0.3(USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6. RNA-seq\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTranscriptome sequencing and analysis were performed by the BGI Company (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bgitechsolutions.com\u003c/span\u003e\u003c/span\u003e). Total RNA was extracted following the manufacturer\u0026apos;s protocol with TRIzol reagent (Invitrogen, CA), dissolved in RNA-free H\u003csub\u003e2\u003c/sub\u003eO and stored at -80\u0026deg;C. Total RNA was processed by mRNA enrichment: The mRNA with polyA tail was enriched by magnetic beads with OligodT. The RNA obtained was segmented by interrupting buffer, and the random N6 primers were reversely transcribed, and then the cDNA two-strand was synthesized to form double-stranded DNA. The synthetic double-stranded DNA ends are flattened and phosphorylated at the 5\u0026apos; end to form A sticky end protruding an \u0026quot;A\u0026quot; at the 3\u0026apos; end, followed by A bubbling-like connector protruding A \u0026quot;T\u0026quot; at the 3\u0026apos; end. The ligands were amplified by PCR using specific primers. The PCR product was thermally denatured into single strand, and then the single strand DNA was cycled with a bridge primer to obtain a single strand circular DNA library. The constructed library was inspected and sequenced after qualified. The resulting data are referred to as RAW reads or RAW data, and the RAW reads are then subjected to quality control (QC) to determine whether the sequenced data are suitable for subsequent analysis. After quality control, the filtered clean reads were compared to the reference sequence. After alignment, the distribution of alignment rate and reads on the reference sequence was counted to determine whether alignment results passed the second QC of alignment. If passed, gene quantitative analysis was carried out and differential gene expression among screened samples will be conducted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7. Immunohistochemistry staining\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTissue slides were deparaffinized in xylene and rehydrated in alcohol. Then, antigen retrieval was performed with 0.1 M sodium citrate buffer. Subsequently, the sections were blocked by performing IHC kit(Maixin China) and probed with primary antibodies for 1 h at room temperature. Slides were incubated with poly-HRP secondary antibodies by performing IHC kit, after which sections were counterstained with haematoxylin to visualize nuclei. Images were analyzed by using Image J v1.8.0(National Institutes of Health, USA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e8. Animal experiment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll mice were maintained at Zhongnan Hospital of Wuhan University and all animal experiments were performed in accordance with Zhongnan Hospital animal ethics committee(Wuhan, China). Male BABL/c nude mice (4 weeks old) were purchased from Gempharmatech (Zhejiang, China). Hep2 cells were resuspended at 2\u0026times;10\u003csup\u003e7\u003c/sup\u003e cells/mL using saline, and each mouse was subcutaneously injected 200 \u0026micro;L into the right anterior flank. After 8 days, the mice were randomly divided into treatment group and control group(5 mice per group). The treatment group was treated with ISO-1(2.5 mg/kg, intraperitoneally, every day) and the control group was treated with saline(equal volume per weight, intraperitoneally, every day). Tumor volume was measured using a caliper every other day, and volumes were calculated using the standard formula: V\u0026thinsp;=\u0026thinsp;0.5*length*width\u003csup\u003e2\u003c/sup\u003e. Finally, mice were euthanized, and tumors were removed, photographed, weighed and collected for ELISA and immunohistochemistry.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e9. Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data were represented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations (SD). All differences between two independent groups were analyzed using Students\u0026rsquo; t test. SPSS 20.0 software (IBM Corporation, USA) was used for statistical analysis. A \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eHypoxia affects lipid metabolism in Hep2 cells\u003c/h2\u003e \u003cp\u003eHypoxia inducible factor 1 subunit alpha (HIF1A), which is an adaptive factor in the hypoxic environment, was found higher expressed when Hep2 cells exposed hypoxic environment as 1% O\u003csub\u003e2\u003c/sub\u003e(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). To make sure whether hypoxia affects HNSCC lipid metabolism, Triglycerides (TG), which is a constituent of lipids, were detected. We found that hypoxia evidently increased the TG level of Hep2 cells(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Besides, non-esterified free fatty acids (NEFA) are the major component of triglycerides, we also found that hypoxia increased NEFA level in Hep2 cells(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Furthermore, we found that the expression pattern of some lipid metabolism related genes was changed, the expressions of PPARA, PPARG, SREBF1, FASN, PPARD were downregulated, and LPIN2 was upregulated when exposed to hypoxia(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). According to these findings, it suggested that hypoxia may make a role in regulating lipid metabolism in HNSCC cells.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMIF may be a key factor in hypoxia regulating lipid metabolism\u003c/h2\u003e \u003cp\u003eAs hypoxia is a common feature of solid tumors, cancer cells confront the compound challenges of high growth rates and limited and unreliable supply of O\u003csub\u003e2\u003c/sub\u003e, therefore cancer cells change the pattern of metabolism to adapt to hyperproliferation. To explore whether lipid metabolism is involved when laryngeal cancer exposed to hypoxia microenvironment, we analyzed the hypoxia gene sets and fatty gene sets, three genes such as Lactate dehydrogenase A (LDHA), enolase 2 (ENO2) and macrophage migration inhibitory factor (MIF) may be involved in lipid metabolism in laryngeal cancer(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). In consistent with the intersection of the hypoxia gene sets and fatty gene sets by bioinformatics analysis, hypoxia significantly upregulated the expression of LDHA, ENO2 and MIF(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). As MIF is a classical\u0026ensp;pro-inflammatory cytokine that is secreted by immune cells and certain other cell types, we found that the protein level of MIF is increased when exposed to hypoxia. Since MIF is also a key factor in lipid metabolism disturbance, we hypothesized that MIF signaling may play a great role in hypoxia-inducing lipid metabolic disorder. To verify whether MIF is the main factor in hypoxia affecting lipid metabolism, ISO-1, a MIF antagonist was used. We found that 25\u0026micro;M ISO-1 significantly inhibited the protein level of MIF, and in the condition of hypoxic environment(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC,\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD), ISO-1 evidently decreased the TG level of Hep2 cells (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01)(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE), and NEFA level of Hep2 cells is slightly decreased, though the statistical analysis showed no difference (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05)(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). To further verify the role of MIF in lipid metabolism, we found that ISO-1 reversed the expression of lipid metabolism related genes(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eJAK/STAT signaling is involved in MIF regulating pathways in laryngeal cancer\u003c/h2\u003e \u003cp\u003eGSEA analysis was used to screen the pathways which are involved in MIF regulating pathways in laryngeal cancer(Gene sets enriched in phenotype l (251 samples)), we found that the top 10 pathways were JAK STAT SIGNALING PATHWAY, ADHERENS JUNCTION, ARRHYTHMOGENIC RIGHT VENTRICULAR CARDIOMYOPATHY ARVC, ECM RECEPTOR INTERACTION, HUNTINGTONS DISEASE, ALZHEIMERS DISEASE, OXIDATIVE PHOSPHORYLATION, PARKINSONS DISEASE, GLUTATHIONE METABOLISM and SPLICEOSOME(Table.1). MIF was an upstream modulator of IL-6 and the IL-6/JAK/STAT pathway has a key role in the growth and development of many human cancers. Thence we hypothesized that hypoxia inducing MIF regulating lipid metabolism may through activating IL-6/JAK/STAT signaling(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). 14 genes were found to be consistent by the intersection of JAK/STAT pathway gene sets and RNA-seq(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). RT-qPCR was used to verify and the gene expression profile is basically consistent with the analysis(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC), confirming that hypoxia activated JAK/STAT signaling pathway.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eHypoxia induces MIF regulating lipid metabolism through activating IL-6/JAK/STAT signaling\u003c/h2\u003e \u003cp\u003eWhen exposed to hypoxia, the mRNA and protein levels of IL-6 were increased(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA,\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). ISO-1 significantly reversed hypoxia inducing IL-6 upregulation(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC,\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). RT-qPCR assay was applied to test the mRNA expression of JAK/STAT pathway genes, it revealed that ISO-1 reversed the expression pattern of JAK/STAT pathway genes profile, suggesting hypoxia activating IL-6/JAK/STAT pathway via MIF(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). To further verify that MIF regulating lipid metabolism through activating IL-6/JAK/STAT pathway, JAK inhibitor XL019 was used, we found that XL019 significantly decreased the TG level of Hep2 cells when exposed to hypoxia(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF), it confirmed that inhibition of JAK signaling reversed hypoxia inducing abnormal lipid metabolism.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eMIF antagonist ISO1 inhibits the tumorigenicity of Hep2 cells in vivo\u003c/h2\u003e \u003cp\u003eTo evaluate whether MIF plays a role in tumorigenicity in vivo, we applied ISO1, a MIF antagonist, to tumor-bearing mice. ISO1 significantly inhabited the tumor growth in vivo(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Tumor weight(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB) obviously decreased in mice injected with ISO1 compared with control mice. Furthermore, the positive rate of Ki67, which reflects the proliferation of cells, was obviously lower in the ISO1 treatment group(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). In inconsistent with the results of cell experiment, the concentration of serum IL6(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD) and serum TG(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE) was decreased with ISO1 treatment. To explore the mechanism of cancer cells adapting to hypoxic microenvironment, we conducted RT-qPCR assay to test the mRNA expression of JAK/STAT pathway genes of tumor xenograft tissues. The results were basically accordance with the cellular data(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). In summary, all these results suggest that hypoxia activated IL-6/JAK/STAT pathway via MIF.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eLipids, proteins and nucleic acids are important components of the biological membranes and structure of cells. In addition, lipids are also used for energy storage and metabolism and play important signaling molecular roles in a variety of cellular activities. The regulation of lipid metabolism, such as lipid uptake, synthesis, and hydrolysis, is essential for maintaining cell homeostasis. In the process of tumor progression, the availability of nutrients in the tumor microenvironment is constantly changing, tumor cells alter lipid metabolism to maintain rapid proliferation, survival, metastasis and chemoresistance.\u003c/p\u003e \u003cp\u003eUnder hypoxic conditions, cancer cells increase the utilization of extracellular lipids to meet the demand for bioenergy and biosynthesis and to maintain membrane homeostasis. Fatty acid metabolism maintains tumorigenesis, progression and treatment resistance by enhancing lipid synthesis, storage and catabolism. In addition, tumor cells exhibit plasticity in fatty acid metabolism and respond to extraneous and systemic metabolic signals (such as obesity and tumor therapy) to promote aggressiveness, treatment and resistance to the development of related diseases[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In our study, we found that hypoxia increased TG and NEFA levels in Hep2 cells, and then we screened the fat acid metabolism related genes in hypoxia gene sets of laryngeal cancer. MIF, ENO2 and LDHA were screened as related to lipid metabolism when laryngeal cancer cells exposed to hypoxia, which is consistent with the RNA-seq analysis of Hep2 cells that exposed to hypoxia. MIF is over-expressed and secreted in various cancer cells in particular in response to hypoxia. As a multifunctional inflammatory cytokine, MIF is related to tumorigenesis, angiogenesis and metastasis of many cancer phenotypes. MIF can potentially promote tumorigenesis by inhibiting the classic tumor suppressor gene p53, regulating cell cycle arrest and apoptosis in response to DNA damage[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Besides, inhibition of MIF can reduce the formation of the pre-metastasis microenvironment in the liver and the metastasis of cancer cells[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn recent years, MIF was reported associated with lipid metabolism in multiple diseases. Changes in expression levels of MIF have an important impact on metabolism and immune regulation of adipose cells. MIF deficiency aggravates the effects of energy-rich fructose diet on hepatic lipid accumulation in the mouse liver[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. MIF upregulation reduced lipolysis and increased lipogenic pathways in adipose tissue[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. MIF deficiency reduces chronic inflammation in white adipose tissue[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. We verified that hypoxia inducing increased TG and NEFA levels via upregulating of MIF by antagonist, ISO-1. And ISO-1 reversed the expression pattern of lipid metabolism related genes, such as PPARA, PPARG, SREBF1, FASN, LPIN2. Through subcutaneous xenograft model, we found that tumors was significantly growth-restricted with ISO-1 treatment. Consistently, the serum IL6 and TG levels of mice showed the same trend. However, there were no statistically significant differences possibly due to large individual variations. More mice are needed for a reliable conclusion.\u003c/p\u003e \u003cp\u003eBesides the key role of MIF on the inflammatory cascade and its ability to counteract glucocorticoid-induced anti-inflammatory responses, MIF also participates in regulating malignant phenotypes of various cancers through activating multiple signaling pathways. MIF expression is abnormally increased and supports the proliferation, migration and invasion of breast cancer, gastric cancer, pancreatic cancer and lung cancer cells[\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. MIF acts as an autocrine growth factor involved in cell cycle in pancreatic cancer cells[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In bladder cancer cells, activation of CXCL2/MIF-CXCR2 signaling induced MDSC accumulation and expansion in the bladder cancer microenvironment[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. MIF/CXCR7/AKT pathway drives growth and metastasis in castration-resistant prostate cancer cells[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo further analyze the molecular mechanism of MIF in regulating lipid metabolism, we screened the related pathway through GSEA analysis, and we found the top one pathway is JAK/STAT pathway. Through the intersection of JAK/STAT pathway gene sets and RNA-seq, we screened that 14 genes showed the same expression patterns, and RT-qPCR results basically verified it in vitro and in vivo. Due to large individual variations of each mouse, a part of genes did not show a siganificant difference even though the trend of gene expression in vivo was consistent with the results in vitro. As MIF was an upstream modulator of IL-6, and IL-6 is the classical upstream activator of JAK/STAT pathway, IL-6 binds to its receptor IL-6R, and induces homodimerization and formation of a high affinity receptor complex, activating MAPK, PI3K/AKT pathways, to regulate growth, differentiation, survival and chemoresistance of cancer cells[\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eJAK/STAT signaling pathway is continuously activated and overexpressed in a variety of tumor cells, the continuously activated JAK/STAT pathway in the tumor microenvironment can inhibit the anti-tumor immune response of immune cells, IL-6/JAK/STAT signal has become a hot signal target for tumor therapy[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. MIF promotes the secretion of the inflammatory factor IL-6 in the tumor hypoxic microenvironment, and promotes the malignant progression of laryngeal cancer and changes in lipid metabolism, suggesting that MIF/IL-6/JAK/STAT pathway is expected to provide a new approach for the treatment of laryngeal cancer.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eHNSCC\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehead and neck squamous cell carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eELISA\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eenzyme-linked immunosorbent assay\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eGSEA\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003egene set enrichment analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eIHC\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eimmunohistochemistry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eNEFA\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon-esterified free fatty acids\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eFA\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efatty acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eTG\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etriglycerides\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eHIF1A\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehypoxia inducible factor 1 subunit alpha\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eMIF\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emacrophage migration inhibitory factor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eLDHA\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elactate dehydrogenase A\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cspan type=\"BoldItalic\" class=\"BoldItalic\" name=\"Emphasis\"\u003eENO2\u003c/span\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eenolase 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe animal study was reviewed and approved by the Ethics Committee of Zhongnan Hospital of Wuhan University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following information was supplied regarding data availability: The gene expression profiles containing the clinical follow-up information is available at TCGA website(https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga). The other data used to support the findings of this study are available from the corresponding author upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was partly supported by the National Natural Science Foundation of China (NO. 81902599).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMinlan Yang: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data Curation, Writing-Original Draft. Sa Wu: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Data Curation, Writing-Original Draft. Weisong Cai: Methodology, Validation, Software, Formal analysis, Investigation, Data Curation, Writing-Original Draft. Xiaoping Ming: Resources, Data Curation. Yuhao Zhou: Data Curation, Visualization. Xiong Chen: Writing- Review \u0026amp; Editing, \u0026nbsp;Supervision. All authors have participated sufficiently in the study and approved the final version\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following information was supplied regarding data availability: The gene expression profiles containing the clinical follow-up information is available at TCGA website(https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga). The other data used to support the findings of this study are available from the corresponding author upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eC. Corbet, O. 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McMillan, Therapeutics targeting innate immune/inflammatory responses through the interleukin-6/JAK/STAT signal transduction pathway in patients with cancer, Transl Res, 167 (2016) 61 \u0026ndash; 6, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.trsl.2015.08.013\u003c/span\u003e\u003cspan address=\"10.1016/j.trsl.2015.08.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable.1 GSEA analysis of MIF in laryngeal carcinoma\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"62.73972602739726%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.356164383561644%\"\u003e\n \u003cp\u003e\u003cstrong\u003esetSize\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.917808219178083%\"\u003e\n \u003cp\u003e\u003cstrong\u003eenrichScore\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.438356164383562%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNES\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.547945205479452%\"\u003e\n \u003cp\u003e\u003cstrong\u003epvalue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.73972602739726%\"\u003e\n \u003cp\u003eKEGG_JAK_STAT_SIGNALING_PATHWAY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.356164383561644%\"\u003e\n \u003cp\u003e155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.917808219178083%\"\u003e\n \u003cp\u003e-0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.438356164383562%\"\u003e\n \u003cp\u003e-2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.547945205479452%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.73972602739726%\"\u003e\n \u003cp\u003eKEGG_ADHERENS_JUNCTION\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.356164383561644%\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.917808219178083%\"\u003e\n \u003cp\u003e-0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.438356164383562%\"\u003e\n \u003cp\u003e-2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.547945205479452%\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.73972602739726%\"\u003e\n \u003cp\u003eKEGG_ARRHYTHMOGENIC_RIGHT_VENTRICULAR_CARDIOMYOPATHY_ARVC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.356164383561644%\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.917808219178083%\"\u003e\n \u003cp\u003e-0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.438356164383562%\"\u003e\n \u003cp\u003e-2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.547945205479452%\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.73972602739726%\"\u003e\n \u003cp\u003eKEGG_ECM_RECEPTOR_INTERACTION\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.356164383561644%\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.917808219178083%\"\u003e\n \u003cp\u003e-0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.438356164383562%\"\u003e\n \u003cp\u003e-2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.547945205479452%\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.73972602739726%\"\u003e\n \u003cp\u003eKEGG_HUNTINGTONS_DISEASE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.356164383561644%\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.917808219178083%\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.438356164383562%\"\u003e\n \u003cp\u003e2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.547945205479452%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.73972602739726%\"\u003e\n \u003cp\u003eKEGG_ALZHEIMERS_DISEASE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.356164383561644%\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.917808219178083%\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.438356164383562%\"\u003e\n \u003cp\u003e2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.547945205479452%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.73972602739726%\"\u003e\n \u003cp\u003eKEGG_OXIDATIVE_PHOSPHORYLATION\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.356164383561644%\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.917808219178083%\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.438356164383562%\"\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.547945205479452%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.73972602739726%\"\u003e\n \u003cp\u003eKEGG_PARKINSONS_DISEASE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.356164383561644%\"\u003e\n \u003cp\u003e128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.917808219178083%\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.438356164383562%\"\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.547945205479452%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.73972602739726%\"\u003e\n \u003cp\u003eKEGG_GLUTATHIONE_METABOLISM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.356164383561644%\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.917808219178083%\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.438356164383562%\"\u003e\n \u003cp\u003e2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.547945205479452%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.73972602739726%\"\u003e\n \u003cp\u003eKEGG_SPLICEOSOME\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.356164383561644%\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.917808219178083%\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.438356164383562%\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.547945205479452%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"hypoxia, MIF, lipid metabolism, IL-6/JAK-STAT pathway","lastPublishedDoi":"10.21203/rs.3.rs-1439230/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1439230/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eHypoxia is a common feature of laryngocarcinoma. Alteration in lipid metabolism in hypoxic microenvironment is an important metabolic rewiring phenomenon for malignant cells to maintain their rapid proliferation, which makes most cancers, including laryngocarcinoma, hard to cure. However, the mechanism of lipid metabolism of laryngocarcinoma involved is still unclear. This study aimed to make clear the changes in lipid metabolism of laryngocarcinoma cell under hypoxic condition and explore the relative mechanism.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eHep2 cells were placed in a normoxic or hypoxic environment (5% CO2, 94% N2 and 1% O2) at 37℃ for 24 h. After exposed to hypoxia, lip metabolic indices including TG and NEFA were tested. The mechanism involved in lip metabolism regulation was explored by RNA seq and bioinformatic analysis. MIF inhibitor ISO-1 and JAK inhibitor XL019 were used to verify the mechanism. Finally, tumour xenograft model was applied has further verified these results in vivo.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eHypoxia increased the TG and NEFA levels of Hep2 cells. Three genes, intersection of hypoxia gene sets and fatty gene sets, including MIF, ENO2, and LDHA were screened and verified by qPCR. MIF levels were elevated when exposed to hypoxia. Through GSEA and RNA-seq analysis, JAK/STAT pathway was screened. Hypoxia increased MIF and activated IL-6/JAK/STAT pathway. MIF inhibitor ISO-1 reversed TG levels, IL-6 levels, and reversed the expression pattern of screened genes in JAK/STAT pathway. Tumour xenograft model has further verified these results.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHypoxia induced reprogramming of lipid metabolism in laryngocarcinoma cells through MIF/IL-6/JAK-STAT pathway. This study revealed one mechanism that allows laryngocarcinoma cells adapt to hypoxic tumor microenvironment. Therefore, a drug targeting MIF/IL-6/JAK-STAT pathway might be a promising therapeutic option for the treatment of laryngeal cancer.\u003c/p\u003e","manuscriptTitle":"Hypoxia-Induced MIF Induces Dysregulation of Lipid Metabolism in Laryngocarcinoma Through IL-6/JAK-STAT Pathway","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-03-16 20:54:58","doi":"10.21203/rs.3.rs-1439230/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"108c2a88-9ebe-493d-95e9-48c9d6a18d6e","owner":[],"postedDate":"March 16th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-03-16T20:55:00+00:00","versionOfRecord":[],"versionCreatedAt":"2022-03-16 20:54:58","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1439230","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1439230","identity":"rs-1439230","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}