Simulated microgravity induces HIF-1-dependent pseudohypoxic and glycolytic state in triple- negative breast cancer

Simulated microgravity induces HIF-1-dependent pseudohypoxic and glycolytic state in triple- negative breast cancer | 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 Article Simulated microgravity induces HIF-1-dependent pseudohypoxic and glycolytic state in triple- negative breast cancer Guangyu Ji, Zhenzhen Zhou, Huize Xia, Zhiqun Zhao, Haiquan Lu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7839613/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract With the expansion of commercial spaceflight and space exploration, the microgravity environment provides unparalleled opportunities to fight against challenging diseases. Here, we investigate the impact of simulated microgravity (sMG) on the cellular morphology and metabolic state of triple-negative breast cancer (TNBC). TNBC cells (SUM159 and MDA-MB-231) were exposed to sMG (~0.001 g) using a random positioning machine (RPM) for 1 and 3 days. Transcriptome profiling revealed that sMG induces a “pseudohypoxic” state, characterized by altered expression of genes typically associated with hypoxia, even under normoxic conditions. sMG upregulates HIF-1α protein levels and its target gene expression , and downregulates c-MYC and its target gene expression. In addition, sMG mediates metabolic reprogramming of TNBC cells by upregulating gene expression in glycolysis and downregulating gene expression in glutaminolysis and TCA cycle in a HIF-1-dependent manner. Metabolomic analysis further confirmed activation of glycolytic pathway under sMG. Our findings demonstrate that sMG induces a HIF-1-dependent pseudohypoxic and glycolytic state in TNBC cells and implicate a gravity-responsive HIF-1/c-MYC axis in metabolic control. Biological sciences/Cancer Biological sciences/Cell biology Biological sciences/Molecular biology Simulated microgravity Pseudohypoxia Metabolic reprogramming Hypoxia-inducible factor 1 Triple-negative breast cancer Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Breast cancer is the most commonly diagnosed cancer among women worldwide, with approximately 2.3 million new cases each year, accounting for 11.7% of all cancers 1 . Breast cancer is a heterogeneous disease that includes four major clinicopathological subtypes: Luminal A, Luminal B, human epidermal growth factor receptor 2 (HER2)-positive, and Triple-negative 2 . Standard breast cancer therapies often involve surgical removal of the primary tumor, followed by chemotherapy, radiation, anti-hormone therapy, HER2-targeted therapy, or anti-angiogenic therapy, depending on the tumor type, size, stage, and lymph node metastasis status 3 . Despite significant advances in treatment, breast cancer remains a leading cause of cancer-related death, accounting for an estimated 684,996 annual deaths worldwide 1 . Among these subtypes, triple-negative breast cancer (TNBC) presents a particular challenge for clinical outcomes due to its high aggressiveness and lack of targeted therapies 4 . Therefore, there is an urgent need for innovative therapeutic strategies that harness the potential of emerging technologies to improve TNBC outcomes. As gravitational biology and space medicine rapidly evolve, research on cancer under microgravity conditions is gaining considerable attention. Microgravity environment provides unparalleled opportunities to explore novel aspects of cancer cell behavior and potential treatments. Studies in real and simulated microgravity (sMG) conditions have demonstrated alterations in cytoskeletal architecture, metastatic potential, transcription factors activity, and self-renewal capacity of human pluripotent stem cells 5 – 8 . In breast cancer cells, microgravity environment has been linked to changes in cell invasion, migration, adhesion, cell cycle, apoptosis, and cytoskeletal remodeling 8 – 12 . Metabolic reprogramming, an emerging hallmark of cancer, is exploited by TNBC cells to fulfill bioenergetic and biosynthetic demands, maintain redox balance, and further promote oncogenic signaling, cell proliferation, and metastasis 13 . Two key transcription factors coordinate these metabolic adaptations: hypoxia-inducible factor 1 (HIF-1), which primarily mediates cellular responses to hypoxia (oxygen limitation) by upregulating glycolytic enzymes, and c-MYC, which drives the expression of genes involved in glucose and glutamine metabolism. Previous studies have reported that cooperative or antagonistic interaction between HIF-1 and c-MYC can shape metabolic plasticity and accelerate tumor growth and metastasis 14 , 15 . However, investigations into the effects of microgravity on the metabolic reprogramming of TNBC cells remain limited. In the present study, we investigated the effects of sMG on TNBC cells SUM159 and MDA-MB-231, and observed morphological remodeling, mitochondrial ultrastructural changes, and increased reactive oxygen species (ROS) after sMG exposure. sMG upregulates HIF-1α protein expression and alters expression of genes related to cellular hypoxia and metabolic processes, even under normoxic conditions, leading to the formation of a “pseudohypoxic” state in TNBC. Mechanistically, sMG enhances HIF-1α expression while repressing c-MYC and its metabolic target expression, which results in the suppression of c-MYC-dependent glutaminolysis and a shift towards glycolytic metabolism. Our findings reveal a gravity-responsive HIF-1/c-MYC axis that drives a pseudohypoxic and glycolytic state in TNBC cells. Material and Methods Random Positioning Machine Microgravity conditions were simulated using the “DARC-G” desktop RPM, a specialized 3D clinostat manufactured by SAGE BIOTECH Co., Ltd. It features two rotation axes, enabling three-dimensional rotation and allowing the dispersion of unidirectional gravity in various directions to simulate microgravity environment. The system simulates microgravity condition based on the calculation of spherical motion trajectory of mass points and features real-time monitoring through built in gravity sensors. The “DARC-G” was positioned inside a standard incubator that controlled temperature, humidity, and CO 2 levels, and was connected to sensors via standard electric cables. Cell culture SUM159 cells were maintained in DMEM/F12 (50:50) medium. MDA-MB-231 cells were maintained in Dulbecco’s modified Eagle medium (DMEM). The culture media were supplemented with 10% (vol/vol) fetal bovine serum (FBS) and 1% (vol/vol) penicillin-streptomycin. Cells were cultured at 37°C in a 5% CO 2 , 95% air incubator. sMG cell model stimulation The “DARC-G” desktop RPM was used to establish the in vitro sMG model. Briefly, cells were cultured in a T-25 cell culture flask until reaching 40% confluence. The flask was fully filled with cell culture medium to eliminate air bubbles, and was mounted on the rotating bioreactor at 37°C and 5% CO 2 . The rotation speed was set to 8 rpm maximum and 6 rpm minimum for the outer shaft, and a maximum of 5 rpm and a minimum of 3 rpm for the inner shaft. These conditions were sustained during the cell culture periods of 1 or 3 days. In the control group, the flask was also fully filled with cell culture medium to eliminate air bubbles, and cells were maintained under normal gravity for 1 or 3 days at 37°C in the stationary position. Cells were immediately harvested for subsequent assays at the end of exposure periods. Transmission electron microscopy (TEM) Cells from the control group were collected from 15-cm culture dishes by scraping, while cells from the sMG group were harvested from T-25 culture flasks after 1 or 3 days of sMG exposure by centrifugation at 1000 rpm. All collected cells were immediately fixed in 2.5% glutaraldehyde fixative (pH 7.0-7.5; Servicebio) and incubated at room temperature for 30 minutes in the dark. The samples were then transferred to 4°C for storage until further processing. Ultra-thin sectioning and TEM were subsequently performed by Servicebio Technology Co., Ltd. Intracellular ROS measurement Intracellular ROS levels were assessed using 2',7'-dichlorofluorescein diacetate (DCFH-DA, Sigma-Aldrich), which is oxidized to the fluorescent compound 2',7'-dichlorofluorescein (DCF) in the presence of peroxides. Cells from the control group were harvested by trypsinization, whereas cells from sMG group were collected by centrifugation after 1 or 3 days of sMG exposure. All cells were washed with phosphate-buffered saline (PBS) and subsequently incubated with 10 µM DCFH-DA at 37°C for 30 minutes in the dark. After incubation, cells were washed twice with PBS and filtered through a 75 µm nylon cell strainer (200 mesh; Solarbio) to obtain single-cell suspensions. DCF fluorescence was analyzed in the FITC channel using a CytoFLEX S flow cytometer (Beckman Coulter). Data were obtained from three independent experiments. RNA extraction and reverse transcription-quantitative PCR (RT-qPCR) Total RNA was extracted using TRIzol reagent (ThermoFisher). cDNA was synthesized using a HiFiScript cDNA Synthesis Kit (CWBIO). Then, cDNAs were amplified using quantitative PCR (qPCR) on a CFX96™ instrument (Real-Time System; Bio-Rad) with the following thermocycling conditions: 95°C for 10 minutes, followed by 40 cycles at 95°C for 15 seconds and 60°C for 60 seconds. Cycle threshold values were normalized to the internal control 18s. The relative expression levels of mRNAs were quantified using the 2 −ΔΔCq method. Primer sequences are shown in Table 1 . Table 1 Primer sequences 18S F: CGGCGACGACCCATTCGAAC R: GAATCGAACCCTGATTCCCCGTC HIF1A F: GAACGTCGAAAAGAAAAGTCTCG R: CCTTATCAAGATGCGAACTCACA MYC F: GCTGCTTAGACGCTGGATTT R: TAACGTTGAGGGGCATCG BNIP3 F: TCCAGCCTCGGTTTCTATTT R: AGCTCTTGGAGCTACTCCGT NDRG1 F: AAGATGGCGGACTGTGGC R: TCAGGCGGGTCATGCTAG PDK1 F: ACCAGGACAGCCAATACAAG R: CCTCGGTCACTCATCTTCAC ANGPTL4 F: GGACACGGCCTATAGCCTG R: CTCTTGGCGCAGTTCTTGTC CD73 F: GCCTGGGAGCTTACGATTTTG R: TAGTGCCCTGGTACTGGTCG CD47 F: AGAAGGTGAAACGATCATCGAGC R: CTCATCCATACCACCGGATCT ALDOA F: CAGGGACAAATGGCGAGACTA R: GGGGTGTGTTCCCCAATCTT GAPDH F: CCATCACCATCTTCCAGGAG R: ATGATGACCCTTTTGGCTCC PKM F: CTGAAGGCAGTGATGTGGCC R: ACCCGGAGGTCCACGTCCTC TPI1 F: AGTGACTAATGGGGCTTTTACTG R: GCCCAATCAGCTCATCTGACTC LDHA F: ATCTTGACCTACGTGGCTTGGA R: CCATACAGGCACACTGGAATCTC RPL13A F: GCCATCGTGGCTAAACAGGTA R: GTTGGTGTTCATCCGCTTGC ASCT2 F: CCGCTTCTTCAACTCCTTCAA R: ACCCACATCCTCCATCTCCA SRM F: GTGGTGGCCTATGCCTACTG R: CTCCTGGAAGTTCGTGCTCG AIMP2 F: GGTTTGCGTTGATCACAATG R: AGTTGAAGGCAGCAGTCGAT DKC1 F: ATGGCGGATGCGGAAGTAAT R: CCACTGAGACGTGTCCAACT Immunoblot assay Cell clumps under sMG and adherent cells under ground control were collected and lysed in RIPA buffer (Beyotime) with protease inhibitors. Proteins were separated using SDS-polyacrylamide gel electrophoresis and transferred to 0.22 μm polyvinylidene difluoride (PVDF) membranes. The membranes were incubated with 5% skim milk for 2 hours at room temperature and incubated with the primary antibodies at 4 °C overnight (supplemental Table 2). After washing, the membranes were incubated with HRP-conjugated secondary antibodies for 1 hour at room temperature. Protein expression was detected with Immobilon™ Western Chemiluminescent HRP Substrate (Millipore), and band intensities were analyzed using ImageJ software. Table 2 lists the specific antibodies employed in this study along with their corresponding catalog numbers. Table 2 Primary antibody information for immunoblot assays Antibody Manufacture Catalog # HIF-1α Cell Signaling Technology #36169 c-MYC Proteintech 67447-1-Ig BNIP3 Proteintech 68091-1-Ig PDK1 Proteintech 18262-1-AP LDHA Proteintech 19987-1-AP β-actin Proteintech 66009-1-Ig HRP-conjugated goat anti-mouse TransGen Biotech HS201-01 HRP-conjugated goat anti-rabbit TransGen Biotech HS101-01 Lentiviral transduction pLKO.1-puro lentiviral shuttle vectors encoding shRNA targeting HIF-1α (ORIGENE; sequences are shown in Table 3 ) were transfected into HEK293T cells for packaging. SUM159 and MDA-MB-231 cells were transduced with viral supernatant for 48 hours and then selected in medium containing puromycin (MilliporeSigma; 0.3 µg/ml for SUM159; 1 µg/ml for MDA-MB-231) to establish stable knockdown subclones. Table 3 shRNA nucleotide sequences encoded in lentiviral vectors HIF-1α #1 TACGTTGTGAGTGGTATTATTCAGCACGA HIF-1α #2 ACAAGAACCTACTGCTAATGCCACCACTA Whole transcriptome analysis by RNA sequencing (RNA-seq) Whole transcriptome analysis was carried out in SUM159 and MDA-MB-231 cells under sMG and normal gravity control conditions to identify differentially expressed genes (DEGs). RNA was extracted using TRIzol reagent. Library preparation and sequencing using the DNBSEQ platform (MGI) were performed by BGI Genomics. RNA-seq data were processed and analyzed using Dr. Tom online platform ( http://report.bgi.com ). Sequencing data were filtered with SOAPnuke and clean reads were mapped to the human reference genome using Bowtie2. Gene expression levels were calculated by RSEM (v1.3.1) and differential expression analysis was performed using the DESeq2 (v1.4.5). Metabolome analysis Metabolomic profiling was performed by BGI Genomics using a Waters UPLC I-Class Plus system (Waters) coupled with a Q Exactive high-resolution mass spectrometer (Thermo Fisher Scientific). Data were acquired in both positive and negative ionization modes. Raw mass spectrometry data were processed with Compound Discoverer 3.3 (Thermo Fisher Scientific) and annotated against multiple databases, including BGI Metabolome Database (BMDB), mzCloud, ChemSpider, and the Human Metabolome Database (HMDB). Differential metabolites were identified based on a fold-change threshold of > 1.5 or < 0.8. Pathway enrichment analysis of significantly altered metabolites was conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database via the MetaboAnalyst platform ( https://new.metaboanalyst.ca/MetaboAnalyst/home.xhtml ). Statistical analysis GraphPad Prism version 8 (GraphPad Software, Inc.) was used for statistical analysis. Comparisons between two groups were analyzed using two-tailed Student’s t -test. Comparisons among multiple groups were analyzed by one-way ANOVA followed by Dunnett’s post hoc test. Data are presented as the mean ± SEM of biological replicates. p < 0.05 was considered statistically significant. Results Simulated microgravity alters morphology, mitochondrial ultrastructure, and ROS levels in TNBC cells. To investigate the effect of microgravity on TNBC cells, we exposed TNBC cells SUM159 and MDA-MB-231 to sMG for 1 or 3 days. sMG was generated using the “DARC-G” desktop RPM, which is composed of a base frame, a supporting frame, an outer frame, and an inner frame that affixed to the outer frame (Fig. 1 a). After sMG exposure, most cell detached from the cell culture flask surface and aggregated to form multicellular spheroids that suspended in the culture medium (Fig. 1 b-d). TEM analysis revealed distinct changes in the mitochondrial morphology following sMG exposure. Mitochondria in normal gravity control cells exhibited typical ovoid structures with intact double membranes and well-organized cristae (Fig. 1 e). In contrast, sMG-treated cells displayed pronounced ultrastructural alterations, including mitochondrial swelling, fragmented cristae, loss of matrix density, and membrane discontinuity. Quantitative analysis demonstrated a significant increase in mitochondrial number per cell, cross-sectional area, average length, and Feret ratio (indicative of elongation) in sMG-treated cells compared to control (Fig. 1 f). Notably, mitochondrial damage severity was attenuated at day 3 relative to day 1, with partial restoration of cristae organization and reduced swelling. Flow cytometry using DCFH-DA staining revealed elevated ROS levels in sMG-treated SUM159 and MDA-MB-231 cells compared to control, as reflected by increased mean fluorescence intensity (MFI) (Fig. 1 g and 1 h). Taken together, these data demonstrate that sMG induces profound morphological alteration, mitochondrial damage, and ROS accumulation in TNBC cells Simulated microgravity triggers gene expression profile associated with cellular hypoxic response. We next examined how microgravity influences gene expression in TNBC cells. SUM159 and MDA-MB-231 cells were cultured under control or sMG conditions for 1 or 3 days, and transcriptomic analysis was performed by RNA sequencing (RNA-seq). In SUM159 cells, compared with control group, we identified a total of 3,228 differentially expressed genes (DEGs) in cells exposed to sMG for 1 day. Among these, 1,744 genes were upregulated and 1,484 genes were downregulated (Fig. 2 a). In MDA-MB-231 cells, a total of 2,930 DEGs were identified after 1-day sMG exposure, with 1,607 genes upregulated and 1,323 genes downregulated (Fig. 2 b). Gene Ontology (GO) enrichment analysis of the common 1,050 DEGs in both cells (Fig. 2 c) revealed a significant enrichment of GO terms associated with hypoxic response and metabolic processes (Fig. 2 d and 2 e). In addition, gene set enrichment analysis (GSEA) of BioCarta and KEGG pathways demonstrated that cells exposed to 1-day sMG exhibited higher expression levels of genes associated with hypoxia pathway compared to cells in control group (Fig. 2 f and 2 g). We also analyzed RNA-seq results of cells exposed to sMG for 3 days. In SUM159 cells, a total of 2,438 genes were upregulated and 5,245 genes were downregulated (Fig. 2 h), and in MDA-MB-231 cells, a total of 1,649 genes were upregulated and 1,109 genes were downregulated, with 3-day sMG exposure (Fig. 2 i). GO enrichment analysis of the common 1,704 DEGs in SUM159 and MDA-MB-231 (Fig. 2 j) revealed that pathways related to hypoxic response and metabolic processes were also enriched after 3-day sMG exposure (Fig. 2 k and 2 l). Consistently, GSEA confirmed significant enrichment of hypoxia pathway in 3-day sMG-exposed TNBC cells (Fig. 2 m and 2 n). Taken together, these data demonstrate that sMG mediates changes of gene expression that are associated with cellular hypoxic response in TNBC. Simulated microgravity increases HIF-1α protein level and promotes HIF-1 target genes expression. Our transcriptome data suggested that sMG induces a hypoxia-like (pseudohypoxic) response despite normal oxygen levels. Therefore, we hypothesized that sMG might activate HIF-1 and its downstream targets. To test this hypothesis, we referenced two hypoxia-related gene sets from the literature 16 , 17 , and assessed the expression profile of these genes under sMG in our RNA-seq data. We found that hypoxia-related genes were induced by 3-day exposure to sMG in both cell lines (Fig. 3 a and 3 b). We next examined the mRNA levels of several classical HIF-1 target genes, including NDRG1, BNIP3, PDK1, CD73, CD47 and ANGPTL4 , under sMG conditions, and found that 3-day sMG exposure increased the expression of most of HIF-1 target genes in both cell lines (with the exception of CD47 in MDA-MB-231) (Fig. 3 c and 3 d). In agreement with the transcriptional data, sMG exposure also increased HIF-1α protein levels in both cell lines (Fig. 3 e). To determine whether the effects observed under sMG are attributable to microgravity itself rather than simply three-dimensional culture conditions, we performed parallel experiments by culturing cells as adherent monolayers or as mammospheres under normal gravity. Representative images confirmed the formation of distinct mammospheres in both SUM159 and MDA-MB-231 cell lines under normal gravity culture (Fig. 3 f). We then quantified the mRNA expression of HIF-1A and its canonical target genes by qPCR. Interestingly, mammosphere formation under normal gravity was associated with a significant decrease in the expression of HIF-1A and most of its downstream targets compared with adherent cells in both cell lines (Fig. 3 g and 3 h). These results demonstrate that the upregulation of HIF-1 signaling observed under sMG is not a generic consequence of three-dimensional culture. Rather, the induction of HIF-1α and its target genes is a specific response to microgravity exposure. Taken together, these data demonstrate that sMG activates HIF-1 signaling and establishes a pseudohypoxic transcriptional state in TNBC cells. Simulated microgravity suppresses MYC and its target genes. We next investigated the effects of sMG on MYC signaling in TNBC cells. RNA-seq analyses revealed a marked and consistent downregulation of multiple MYC target genes in both SUM159 and MDA-MB-231 cells after 1 and 3 days of sMG exposure, relative to normal gravity control (Fig. 4 a and 4 b). To validate these findings, we performed RT-qPCR for mRNA levels of MYC and several representative downstream targets, including ASCT2, SRM, AIMP2 , and DKC1 18,19 . Consistent with the RNA-seq data, sMG exposure for 1 or 3 days significantly decreased mRNA levels of MYC and its target genes in SUM159 and MDA-MB-231 cells (Fig. 4 c and 4 d). Western blot analysis further confirmed that c-MYC protein levels were decreased after sMG exposure for 1 or 3 days in both cell lines (Fig. 4 e). Taken together, these data demonstrate that sMG suppresses MYC expression at both mRNA and protein levels, and downregulates the MYC transcriptional program in TNBC cells. HIF-1 is required for sMG-induced pseudohypoxic response and MYC suppression. HIF-1 is the master regulator of cellular response to hypoxia 20 .To determine whether HIF-1 is necessary for the pseudohypoxic gene response induced by sMG, we generated stable HIF-1α knockdown and non-targeting control (NTC) subclones in SUM159 and MDA-MB-231 cells. In NTC subclones, sMG exposure for 1 or 3 days significantly increased mRNA levels of classical hypoxia-response genes, such as PDK1 and ALDOA , but decreased mRNA level of MYC . These sMG-mediated changes were dramatically attenuated in HIF-1α knockdown subclones (Fig. 5 a and 5 b). Consistently, sMG treatment markedly increased HIF-1α, BNIP3, and LDHA protein levels, and decreased c-MYC protein levels, in NTC cells. HIF-1α knockdown not only abrogated sMG-mediated upregulation of BNIP3 and LDHA, but also partially reversed sMG-mediated suppression of c-MYC (Fig. 5 c and 5 d). These results indicate that HIF-1 is required for sMG-induced pseudohypoxic gene expression and for sMG-driven c-MYC repression. Simulated microgravity drives metabolic reprogramming in TNBC cells. Finally, we examined whether sMG alters metabolic phenotype in TNBC cells. Metabolomic profiling was performed on cell culture supernatants from SUM159 and MDA-MB-231 cells after 1 or 3 days of sMG exposure. Using a cutoff of > 1.5-fold increase or < 0.8-fold decrease, we identified metabolites that were changed by sMG. A Venn diagram analysis of differentially regulated metabolites in SUM159 and MDA-MB-231 cells at day 1 and day 3 of sMG exposure identified a set of common changing metabolites (Fig. 6 a). KEGG pathway analysis of these common differential metabolites in SUM159 and MDA-MB-231 cells showed significant enrichment in pathways associated with the TCA cycle, glycolysis, glutathione metabolism, and amino acid metabolism, with a largely consistent metabolic profile at both day 1 and day 3 (Fig. 6 b). To further explore sMG-induced metabolic changes, we examined expression of genes involved in glycolysis, glutaminolysis, and the TCA cycle 21 . Heatmaps of RNA-seq data demonstrated a robust upregulation of glycolytic genes, whereas the majority of genes involved in glutaminolysis and the TCA cycle were downregulated after 3 days of sMG exposure (Fig. 6 c-h). These transcriptomic findings were validated by RT-qPCR, which confirmed the induction of key glycolytic genes, including ALDOA , TPI1 , GAPDH , PKM , and LDHA , after sMG exposure for 3 days (Fig. 6 i). Taken together, these data indicate that sMG drives metabolic reprogramming in TNBC cells, characterized by enhanced glycolysis and suppressed oxidative metabolism. Discussion TNBC is the most aggressive subtype of breast cancer with limited targeted treatment options and a high propensity for metastasis. There is a continuous pursuit of more effective treatment strategies for TNBC 22 – 24 . In this study, we have demonstrated that sMG induces a coordinated cellular program in TNBC cells that includes morphological remodeling, mitochondrial perturbation, ROS accumulation, and a transcriptional switch towards a HIF-1-dependent pseudohypoxic and glycolytic state. These observations support a model in which altered gravitational signals are transduced into metabolic control through the HIF‑1/c‑MYC axis. Previous studies have reported that real or simulated microgravity induces notable morphologic changes in various cell types, such as osteoblasts 25 , 26 . Consistent with those findings, we have observed that most TNBC cells aggregate into multicellular spheroids and suspend in the culture medium when exposed to sMG. This phenomenon is supported by established 3D culture models 27 and has been highlighted as a key area of investigation in breast cancer research under microgravity 28 . In addition to morphological changes, we have observed that mitochondria, which are central to metabolism and redox homeostasis 29 and whose dynamics are recognized as a therapeutic target in TNBC 30 , are particularly sensitive to microgravity. Remarkably, the extent of mitochondrial damage is alleviated after prolonged sMG exposure, as evidenced by partial cristae restoration, suggesting mitochondrial plasticity and adaptive quality control mechanisms 31 . Such adaptation likely supports cell survival under sustained stress by promoting metabolic reprogramming toward glycolysis 32 and limiting excessive ROS production. These findings underscore the dynamic organellar responses and cellular plasticity of TNBC cells under microgravity, highlighting mitochondria as critical mediators of adaptation to altered gravitational environments. Transcriptomic analysis have revealed a pseudohypoxic gene expression pattern in TNBC cells under sMG conditions. Specifically, sMG triggers metabolic reprogramming in TNBC cells, characterized by upregulation of glycolysis-related gene and downregulation of TCA cycle-related genes in a HIF-1-dependent manner. This highlights the well-established role of HIF-1 in promoting glycolytic flux while suppressing mitochondrial respiration 33 . Furthermore, the repression of c-MYC-driven oxidative metabolism and glutaminolysis highlights the well-established antagonistic relationship between HIF-1 and c-MYC in regulating metabolic pathways 34 . These findings highlight the critical role of HIF-1 in sensing gravity signals and orchestrating transcriptional reprogramming and three-dimensional growth of TNBC cells in response to sMG, even in the presence of adequate oxygen. Further analysis of transcriptional networks under sMG conditions indicates that hypoxia-related pathways are significantly enriched, alongside increased protein levels of the HIF-1α subunit. These transcriptomic changes contribute to a metabolic shift that appears to prioritize glycolysis over mitochondrial oxidative metabolism. Moreover, in line with the critical role of HIF-1 in promoting glycolysis in response to sMG, HIF-1 activation also represses c-MYC-driven oxidative metabolism and glutaminolysis, further potentiating the glycolytic phenotype. This discovery demonstrates a novel role of HIF-1 as a key regulator in the cellular response to changes of gravity, expanding our understanding of this important transcription factor beyond its traditional function as an oxygen sensor. Although RPM devices are widely used to simulate microgravity environment, residual accelerations, fluid dynamics, and shear stress can influence cellular behavior 35 , 36 . In our experiments, to reduce fluid shear, cells were cultured in the flasks fully filled with medium for both sMG and normal gravity controls. Importantly, three-dimensional mammosphere growth at normal gravity did not recapitulate HIF-1 activation, indicating that our observations reflect gravity perturbation rather than three-dimensional culture per se. This distinction is supported by studies showing the unique physiological properties of microgravity-induced 3D constructs 37 . However, quantitative characterization of residual gravity and shear stress in our setup, inclusion of hardware rotation controls, and direct measurements of intracellular oxygen tension and prolyl-hydroxylase activity 38 would further strengthen causal link between microgravity and the observed cellular responses. Additional TNBC models and in vivo validation studies, including spaceflight or partial‑gravity analogs, are warranted to generalize these findings 39 . In conclusion, our data demonstrate a gravity‑responsive HIF‑1/c‑MYC module as a central regulator of the metabolic state in TNBC (Fig. 7 ). These findings expand the role of HIF‑1 from an oxygen sensor to a gravity‑responsive node that coordinates transcriptional and metabolic adaptation. By coupling biophysical perturbation with targeted metabolic therapy, our work suggests new opportunities to exploit the vulnerabilities of TNBC. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials All data and materials are available under the requirement to the corresponding authors. Competing interests The authors declare no competing interests. Funding This work was supported by National Natural Science Foundation of China (Overseas Excellent Young Scientist Fund Program to H.L.; 82473126 to H.L.), Natural Science Foundation of Shandong Province (ZR2021YQ50 to H.L.; ZR2022QC212 to G.J.), Cutting Edge Development Fund of Advanced Medical Research Institute at Shandong University (GYY2023QY01 to H.L.), and Instrument Development Project of Shandong University (zy20250302 to H.L.).Haiquan Lu is a Taishan Scholar Young Talent Professor of Shandong Province and Distinguished Young Professor at Shandong University. Authors' contributions G.J. and H.L. designed the research study. G.J. and Z.Z. performed the experiments and acquired data, H.X. and Z.Z. performed statistical analyses. G.J., Z.Z. and H.L. analyzed the data and wrote the manuscript. H.L. supervised the study. Acknowledgements We thank Translational Medicine Core Facility of Shandong University for consultation and instrument availability that supported this work. 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Recent studies of the effects of microgravity on cancer cells and the development of 3D multicellular cancer spheroids. Stem Cells Transl. Med. 14 , szaf008 (2025). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 11 Mar, 2026 Reviews received at journal 25 Feb, 2026 Reviews received at journal 25 Feb, 2026 Reviews received at journal 16 Feb, 2026 Reviewers agreed at journal 12 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers agreed at journal 24 Dec, 2025 Reviewers invited by journal 11 Dec, 2025 Editor assigned by journal 01 Dec, 2025 Submission checks completed at journal 20 Oct, 2025 First submitted to journal 12 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-7839613","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":560087519,"identity":"519a3ea1-d85e-4015-a94b-562a008b03e1","order_by":0,"name":"Guangyu Ji","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Guangyu","middleName":"","lastName":"Ji","suffix":""},{"id":560087521,"identity":"a047f526-b85d-4d6d-9e22-b0e0be44d829","order_by":1,"name":"Zhenzhen Zhou","email":"","orcid":"","institution":"Shandong 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cells cultured under sMG.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(c and d)\u003c/strong\u003eMicrophotographs of SUM159 (c) and MDA-MB-231 (d) cells cultured under normal gravity control (Ctrl) or exposed to sMG for 1 or 3 days. Scale bar = 100 µm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(e)\u003c/strong\u003eRepresentative TEM images of MDA-MB-231 cells after 1 or 3 days under Ctrl or sMG. Lower panels show magnified views of the boxed regions in the upper panels. Red arrows indicate mitochondria with ultrastructural damage. Scale bars = 5 μm (top), 2 μm (middle) and 500 nm (bottom).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(f)\u003c/strong\u003e Quantification of mitochondrial number per cell (n = 4), average length (n = 23), area (n = 23) and Feret ratio (n = 23). Data are presented as mean ± SEM.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(g and h)\u003c/strong\u003e Flow cytometry analysis of intracellular ROS levels in SUM159 (g) and MDA-MB-231 (h) cells using DCFH-DA staining. Data are presented as mean ± SEM (n = 3). *, p \u0026lt; 0.05; **, p \u0026lt; 0.01; ***, p \u0026lt; 0.001; ****, p \u0026lt; 0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7839613/v1/2b4041dfa1d446c180503e0b.png"},{"id":98336166,"identity":"ae1f2710-674e-4677-a981-b061fba1497f","added_by":"auto","created_at":"2025-12-16 16:23:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":828903,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSimulated microgravity triggers gene expression profile associated with cellular hypoxic response.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a, b, h and i)\u003c/strong\u003e Volcano plots of differentially expressed genes (DEGs) from RNA-seq of SUM159 or MDA-MB-231 cells exposed to sMG or Ctrl for 1 or 3 days. Red and blue dots represent up-regulated and down-regulated genes, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(c and j) \u003c/strong\u003eVenn diagrams of DEGs in SUM159 and MDA-MB-231 cells after 1 day (c) or 3 days (j) of sMG, showing the number of common DEGs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(d, e, k and l)\u003c/strong\u003e Gene Ontology (GO) enrichment analyses of the common DEGs from 1-day (d, e) or 3-day (k, l) sMG exposure, showing significantly enriched pathways.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(f, g, m and n)\u003c/strong\u003e Gene set enrichment analysis (GSEA) of hypoxia-associated gene sets in SUM159 and MDA-MB-231 cells exposed to sMG for 1 or 3 days. The plots show profiles of the running enrichment score (ES) and positions of gene set members on the ranked list of genes. NES, normalized enrichment score.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7839613/v1/15e5ccf19e1ae6b47e07d086.png"},{"id":98336165,"identity":"6ab8ddb1-e755-4224-af48-bda06fbcdc27","added_by":"auto","created_at":"2025-12-16 16:23:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1503929,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSimulated microgravity increases HIF-1α protein level and promotes HIF-1 target genes expression.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a and b)\u003c/strong\u003e Heatmaps showing the expression patterns of hypoxia-related gene sets in RNA-seq data in SUM159 (a) and MDA-MB-231 (b) cells under sMG condition after 3 days of sMG. Color scale represents log\u003csub\u003e2\u003c/sub\u003e(fold change).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(c and d)\u003c/strong\u003e RT-qPCR analysis of mRNA levels of HIF-1 target genes (\u003cem\u003eBNIP3, PDK1, NDRG1, CD73, CD47 \u003c/em\u003eand\u003cem\u003e ANGPTL4\u003c/em\u003e) in SUM159 (c) and MDA-MB-231 (d) cells after 3 days of sMG. \u003cem\u003eRPL13A\u003c/em\u003e serves as the negative control gene. Data are presented as mean ± SEM (n = 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(e)\u003c/strong\u003e Western blotting showing HIF-1α protein levels in SUM159 and MDA-MB-231 cells exposed to Ctrl or sMG conditions for 1 or 3 days.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(f)\u003c/strong\u003e Representative images of adherent and mammosphere cultures of SUM159 and MDA-MB-231 cells after 3 days under normoxic (1g) conditions. Scale bars = 100 μm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(g and h)\u003c/strong\u003e RT-qPCR analysis for \u003cem\u003eHIF1A\u003c/em\u003e and its target genes (\u003cem\u003eBNIP3, PDK1, NDRG1, CD73, CD47, ALDOA, TPI1\u003c/em\u003e) in SUM159 (g) and MDA-MB-231 (h) cells cultured under adherent or mammosphere conditions for 3 days. Data are presented as mean ± SEM (n = 3). *, p \u0026lt; 0.05; **, p \u0026lt; 0.01; ***, p \u0026lt; 0.001; ****, p \u0026lt; 0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7839613/v1/0a98c4baf3f26b1f46ef1126.png"},{"id":98438308,"identity":"42c98342-8c0f-4432-95cd-81f961509f36","added_by":"auto","created_at":"2025-12-17 16:58:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":819589,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSimulated microgravity suppresses MYC and its target genes.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a and b)\u003c/strong\u003e Heatmaps showing the expression patterns of MYC target gene sets in RNA-seq data in SUM159 (a) and MDA-MB-231 (b) cells under sMG conditions after 1 or 3 days of sMG. Color scale represents log\u003csub\u003e2\u003c/sub\u003e(fold change).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(c and d)\u003c/strong\u003e RT-qPCR analysis of mRNA levels of \u003cem\u003eMYC\u003c/em\u003e and representative MYC target genes (\u003cem\u003eASCT2, SRM, AIMP2, DKC1\u003c/em\u003e) in SUM159 (c) and MDA-MB-231 (d) cells after 1 or 3 days of sMG. Data are presented as mean ± SEM (n = 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(e)\u003c/strong\u003e Western blot analysis of c-MYC protein in SUM159 and MDA-MB-231 cells exposed to Ctrl or sMG conditions for 1 or 3 days. ***, p \u0026lt; 0.001; ****, p \u0026lt; 0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7839613/v1/0f3197b12b3a2bd3e9b3bb9e.png"},{"id":98336175,"identity":"c8325d47-4b0f-41a7-9ea0-41bff6592bd1","added_by":"auto","created_at":"2025-12-16 16:23:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1031815,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHIF-1 is required for sMG-induced pseudohypoxic response and MYC suppression.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a and b)\u003c/strong\u003eRT-qPCR analysis of \u003cem\u003eHIF1A, PDK1\u003c/em\u003e, \u003cem\u003eALDOA\u003c/em\u003e, and \u003cem\u003eMYC \u003c/em\u003emRNA levels in SUM159 (a) and MDA-MB-231 (b) cells with non-targeting control (shNTC) or stable HIF-1α knockdown (shHIF-1α #1 and shHIF-1α #2) subclones cultured under Ctrl or sMG conditions for 1 or 3 days.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(c and d)\u003c/strong\u003eWestern blot analysis of HIF-1α, c-MYC, BNIP3, and LDHA protein in SUM159 (c) and MDA-MB-231 (d) cells with NTC or HIF-1α knockdown subclones cultured under Ctrl or sMG conditions for 1 or 3 days. Data are presented as mean ± SEM (n = 3). * p \u0026lt; 0.05, ***p \u0026lt; 0.001, ****p \u0026lt; 0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7839613/v1/d5b46f9370467323d9428de5.png"},{"id":98438156,"identity":"07f98b97-020f-4a6a-b336-0ba20bf14107","added_by":"auto","created_at":"2025-12-17 16:58:43","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1165645,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSimulated microgravity drives metabolic reprogramming in TNBC cells.\u003c/strong\u003e \u003cstrong\u003e(a)\u003c/strong\u003e Venn diagram showing the overlap of significantly altered metabolites in SUM159 and MDA-MB-231 cells after 1 or 3 days of sMG exposure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b)\u003c/strong\u003e KEGG pathway enrichment analysis of the metabolites commonly altered in SUM159 and MDA-MB-231 cells after 1 or 3 days of sMG exposure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(c, d, e, f, g and h)\u003c/strong\u003e Heatmaps of RNA-seq data showing the expression profile of genes involved in glycolysis, glutaminolysis and TCA cycle in SUM159 and MDA-MB-231 cells after 3 days of sMG. Color scale represents log\u003csub\u003e2\u003c/sub\u003e(fold change).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(i)\u003c/strong\u003e RT-qPCR analysis of the expression of genes related to glycolysis (\u003cem\u003eALDOA, TPI1, GAPDH, PKM, LDHA\u003c/em\u003e). Data are presented as mean ± SEM (n = 3). ***, p \u0026lt; 0.001; ****, p \u0026lt; 0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-7839613/v1/58b0e84d6f8899f6fb0e479c.png"},{"id":98336172,"identity":"5ca67439-e96b-4b84-bd90-0fe1569054ac","added_by":"auto","created_at":"2025-12-16 16:23:07","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":325115,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSimulated microgravity induces HIF-1-dependent pseudohypoxic and glycolytic state in TNBC.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003esMG stimulates a pseudohypoxic transcriptional program in TNBC cells via modulating the HIF-1/c-MYC axis, which orchestrates glycolytic, glutaminolytic, and oxidative metabolic reprogramming.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-7839613/v1/b1dd93fea2d13ae42936b978.png"},{"id":98623754,"identity":"e6a93e46-3291-44d7-92a4-c44dfab72c87","added_by":"auto","created_at":"2025-12-19 17:07:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9310208,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7839613/v1/55a64d87-f101-417a-b6f1-d8996acc947b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Simulated microgravity induces HIF-1-dependent pseudohypoxic and glycolytic state in triple- negative breast cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer is the most commonly diagnosed cancer among women worldwide, with approximately 2.3\u0026nbsp;million new cases each year, accounting for 11.7% of all cancers\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Breast cancer is a heterogeneous disease that includes four major clinicopathological subtypes: Luminal A, Luminal B, human epidermal growth factor receptor 2 (HER2)-positive, and Triple-negative\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Standard breast cancer therapies often involve surgical removal of the primary tumor, followed by chemotherapy, radiation, anti-hormone therapy, HER2-targeted therapy, or anti-angiogenic therapy, depending on the tumor type, size, stage, and lymph node metastasis status\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Despite significant advances in treatment, breast cancer remains a leading cause of cancer-related death, accounting for an estimated 684,996 annual deaths worldwide\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Among these subtypes, triple-negative breast cancer (TNBC) presents a particular challenge for clinical outcomes due to its high aggressiveness and lack of targeted therapies\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Therefore, there is an urgent need for innovative therapeutic strategies that harness the potential of emerging technologies to improve TNBC outcomes.\u003c/p\u003e \u003cp\u003eAs gravitational biology and space medicine rapidly evolve, research on cancer under microgravity conditions is gaining considerable attention. Microgravity environment provides unparalleled opportunities to explore novel aspects of cancer cell behavior and potential treatments. Studies in real and simulated microgravity (sMG) conditions have demonstrated alterations in cytoskeletal architecture, metastatic potential, transcription factors activity, and self-renewal capacity of human pluripotent stem cells\u003csup\u003e\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In breast cancer cells, microgravity environment has been linked to changes in cell invasion, migration, adhesion, cell cycle, apoptosis, and cytoskeletal remodeling\u003csup\u003e\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eMetabolic reprogramming, an emerging hallmark of cancer, is exploited by TNBC cells to fulfill bioenergetic and biosynthetic demands, maintain redox balance, and further promote oncogenic signaling, cell proliferation, and metastasis\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Two key transcription factors coordinate these metabolic adaptations: hypoxia-inducible factor 1 (HIF-1), which primarily mediates cellular responses to hypoxia (oxygen limitation) by upregulating glycolytic enzymes, and c-MYC, which drives the expression of genes involved in glucose and glutamine metabolism. Previous studies have reported that cooperative or antagonistic interaction between HIF-1 and c-MYC can shape metabolic plasticity and accelerate tumor growth and metastasis\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. However, investigations into the effects of microgravity on the metabolic reprogramming of TNBC cells remain limited.\u003c/p\u003e \u003cp\u003eIn the present study, we investigated the effects of sMG on TNBC cells SUM159 and MDA-MB-231, and observed morphological remodeling, mitochondrial ultrastructural changes, and increased reactive oxygen species (ROS) after sMG exposure. sMG upregulates HIF-1α protein expression and alters expression of genes related to cellular hypoxia and metabolic processes, even under normoxic conditions, leading to the formation of a \u0026ldquo;pseudohypoxic\u0026rdquo; state in TNBC. Mechanistically, sMG enhances HIF-1α expression while repressing c-MYC and its metabolic target expression, which results in the suppression of c-MYC-dependent glutaminolysis and a shift towards glycolytic metabolism. Our findings reveal a gravity-responsive HIF-1/c-MYC axis that drives a pseudohypoxic and glycolytic state in TNBC cells.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eRandom Positioning Machine\u003c/h2\u003e \u003cp\u003eMicrogravity conditions were simulated using the \u0026ldquo;DARC-G\u0026rdquo; desktop RPM, a specialized 3D clinostat manufactured by SAGE BIOTECH Co., Ltd. It features two rotation axes, enabling three-dimensional rotation and allowing the dispersion of unidirectional gravity in various directions to simulate microgravity environment. The system simulates microgravity condition based on the calculation of spherical motion trajectory of mass points and features real-time monitoring through built in gravity sensors. The \u0026ldquo;DARC-G\u0026rdquo; was positioned inside a standard incubator that controlled temperature, humidity, and CO\u003csub\u003e2\u003c/sub\u003e levels, and was connected to sensors via standard electric cables.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCell culture\u003c/h3\u003e\n\u003cp\u003eSUM159 cells were maintained in DMEM/F12 (50:50) medium. MDA-MB-231 cells were maintained in Dulbecco\u0026rsquo;s modified Eagle medium (DMEM). The culture media were supplemented with 10% (vol/vol) fetal bovine serum (FBS) and 1% (vol/vol) penicillin-streptomycin. Cells were cultured at 37\u0026deg;C in a 5% CO\u003csub\u003e2\u003c/sub\u003e, 95% air incubator.\u003c/p\u003e\n\u003ch3\u003esMG cell model stimulation\u003c/h3\u003e\n\u003cp\u003eThe \u0026ldquo;DARC-G\u0026rdquo; desktop RPM was used to establish the in vitro sMG model. Briefly, cells were cultured in a T-25 cell culture flask until reaching 40% confluence. The flask was fully filled with cell culture medium to eliminate air bubbles, and was mounted on the rotating bioreactor at 37\u0026deg;C and 5% CO\u003csub\u003e2\u003c/sub\u003e. The rotation speed was set to 8 rpm maximum and 6 rpm minimum for the outer shaft, and a maximum of 5 rpm and a minimum of 3 rpm for the inner shaft. These conditions were sustained during the cell culture periods of 1 or 3 days. In the control group, the flask was also fully filled with cell culture medium to eliminate air bubbles, and cells were maintained under normal gravity for 1 or 3 days at 37\u0026deg;C in the stationary position. Cells were immediately harvested for subsequent assays at the end of exposure periods.\u003c/p\u003e\n\u003ch3\u003eTransmission electron microscopy (TEM)\u003c/h3\u003e\n\u003cp\u003eCells from the control group were collected from 15-cm culture dishes by scraping, while cells from the sMG group were harvested from T-25 culture flasks after 1 or 3 days of sMG exposure by centrifugation at 1000 rpm. All collected cells were immediately fixed in 2.5% glutaraldehyde fixative (pH 7.0-7.5; Servicebio) and incubated at room temperature for 30 minutes in the dark. The samples were then transferred to 4\u0026deg;C for storage until further processing. Ultra-thin sectioning and TEM were subsequently performed by Servicebio Technology Co., Ltd.\u003c/p\u003e\n\u003ch3\u003eIntracellular ROS measurement\u003c/h3\u003e\n\u003cp\u003eIntracellular ROS levels were assessed using 2',7'-dichlorofluorescein diacetate (DCFH-DA, Sigma-Aldrich), which is oxidized to the fluorescent compound 2',7'-dichlorofluorescein (DCF) in the presence of peroxides. Cells from the control group were harvested by trypsinization, whereas cells from sMG group were collected by centrifugation after 1 or 3 days of sMG exposure. All cells were washed with phosphate-buffered saline (PBS) and subsequently incubated with 10 \u0026micro;M DCFH-DA at 37\u0026deg;C for 30 minutes in the dark. After incubation, cells were washed twice with PBS and filtered through a 75 \u0026micro;m nylon cell strainer (200 mesh; Solarbio) to obtain single-cell suspensions. DCF fluorescence was analyzed in the FITC channel using a CytoFLEX S flow cytometer (Beckman Coulter). Data were obtained from three independent experiments.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRNA extraction and reverse transcription-quantitative PCR (RT-qPCR)\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted using TRIzol reagent (ThermoFisher). cDNA was synthesized using a HiFiScript cDNA Synthesis Kit (CWBIO). Then, cDNAs were amplified using quantitative PCR (qPCR) on a CFX96\u0026trade; instrument (Real-Time System; Bio-Rad) with the following thermocycling conditions: 95\u0026deg;C for 10 minutes, followed by 40 cycles at 95\u0026deg;C for 15 seconds and 60\u0026deg;C for 60 seconds. Cycle threshold values were normalized to the internal control 18s. The relative expression levels of mRNAs were quantified using the 2\u003csup\u003e\u0026minus;ΔΔCq\u003c/sup\u003e method. Primer sequences are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimer sequences\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e18S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: CGGCGACGACCCATTCGAAC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: GAATCGAACCCTGATTCCCCGTC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHIF1A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: GAACGTCGAAAAGAAAAGTCTCG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: CCTTATCAAGATGCGAACTCACA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMYC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: GCTGCTTAGACGCTGGATTT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: TAACGTTGAGGGGCATCG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBNIP3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: TCCAGCCTCGGTTTCTATTT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: AGCTCTTGGAGCTACTCCGT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNDRG1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: AAGATGGCGGACTGTGGC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: TCAGGCGGGTCATGCTAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePDK1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: ACCAGGACAGCCAATACAAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: CCTCGGTCACTCATCTTCAC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eANGPTL4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: GGACACGGCCTATAGCCTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: CTCTTGGCGCAGTTCTTGTC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCD73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: GCCTGGGAGCTTACGATTTTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: TAGTGCCCTGGTACTGGTCG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCD47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: AGAAGGTGAAACGATCATCGAGC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: CTCATCCATACCACCGGATCT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eALDOA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: CAGGGACAAATGGCGAGACTA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: GGGGTGTGTTCCCCAATCTT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGAPDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: CCATCACCATCTTCCAGGAG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: ATGATGACCCTTTTGGCTCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePKM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: CTGAAGGCAGTGATGTGGCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: ACCCGGAGGTCCACGTCCTC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTPI1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: AGTGACTAATGGGGCTTTTACTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: GCCCAATCAGCTCATCTGACTC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLDHA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: ATCTTGACCTACGTGGCTTGGA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: CCATACAGGCACACTGGAATCTC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRPL13A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: GCCATCGTGGCTAAACAGGTA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: GTTGGTGTTCATCCGCTTGC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eASCT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: CCGCTTCTTCAACTCCTTCAA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: ACCCACATCCTCCATCTCCA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSRM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: GTGGTGGCCTATGCCTACTG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: CTCCTGGAAGTTCGTGCTCG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAIMP2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: GGTTTGCGTTGATCACAATG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: AGTTGAAGGCAGCAGTCGAT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDKC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF: ATGGCGGATGCGGAAGTAAT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR: CCACTGAGACGTGTCCAACT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eImmunoblot assay\u003c/h3\u003e\n\u003cp\u003eCell clumps under sMG and adherent cells under ground control were collected and lysed in RIPA buffer (Beyotime) with protease inhibitors. Proteins were separated using SDS-polyacrylamide gel electrophoresis and transferred to 0.22 μm polyvinylidene difluoride (PVDF) membranes. The membranes were incubated with 5% skim milk for 2 hours at room temperature and incubated with the primary antibodies at 4 °C overnight (supplemental Table 2). After washing, the membranes were incubated with HRP-conjugated secondary antibodies for 1 hour at room temperature. Protein expression was detected with Immobilon™ Western Chemiluminescent HRP Substrate (Millipore), and band intensities were analyzed using ImageJ software. Table 2 lists the specific antibodies employed in this study along with their corresponding catalog numbers.\u003c/p\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimary antibody information for immunoblot assays\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntibody\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManufacture\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCatalog #\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIF-1α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCell Signaling Technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e#36169\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ec-MYC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67447-1-Ig\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBNIP3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68091-1-Ig\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePDK1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18262-1-AP\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDHA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19987-1-AP\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ-actin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProteintech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66009-1-Ig\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHRP-conjugated goat anti-mouse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTransGen Biotech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHS201-01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHRP-conjugated goat anti-rabbit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTransGen Biotech\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHS101-01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eLentiviral transduction\u003c/h3\u003e\n\u003cp\u003epLKO.1-puro lentiviral shuttle vectors encoding shRNA targeting HIF-1α (ORIGENE; sequences are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) were transfected into HEK293T cells for packaging. SUM159 and MDA-MB-231 cells were transduced with viral supernatant for 48 hours and then selected in medium containing puromycin (MilliporeSigma; 0.3 \u0026micro;g/ml for SUM159; 1 \u0026micro;g/ml for MDA-MB-231) to establish stable knockdown subclones.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eshRNA nucleotide sequences encoded in lentiviral vectors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIF-1α #1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTACGTTGTGAGTGGTATTATTCAGCACGA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHIF-1α #2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACAAGAACCTACTGCTAATGCCACCACTA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eWhole transcriptome analysis by RNA sequencing (RNA-seq)\u003c/h2\u003e \u003cp\u003eWhole transcriptome analysis was carried out in SUM159 and MDA-MB-231 cells under sMG and normal gravity control conditions to identify differentially expressed genes (DEGs). RNA was extracted using TRIzol reagent. Library preparation and sequencing using the DNBSEQ platform (MGI) were performed by BGI Genomics. RNA-seq data were processed and analyzed using Dr. Tom online platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://report.bgi.com\u003c/span\u003e\u003cspan address=\"http://report.bgi.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Sequencing data were filtered with SOAPnuke and clean reads were mapped to the human reference genome using Bowtie2. Gene expression levels were calculated by RSEM (v1.3.1) and differential expression analysis was performed using the DESeq2 (v1.4.5).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMetabolome analysis\u003c/h2\u003e \u003cp\u003eMetabolomic profiling was performed by BGI Genomics using a Waters UPLC I-Class Plus system (Waters) coupled with a Q Exactive high-resolution mass spectrometer (Thermo Fisher Scientific). Data were acquired in both positive and negative ionization modes. Raw mass spectrometry data were processed with Compound Discoverer 3.3 (Thermo Fisher Scientific) and annotated against multiple databases, including BGI Metabolome Database (BMDB), mzCloud, ChemSpider, and the Human Metabolome Database (HMDB). Differential metabolites were identified based on a fold-change threshold of \u0026gt;\u0026thinsp;1.5 or \u0026lt;\u0026thinsp;0.8. Pathway enrichment analysis of significantly altered metabolites was conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database via the MetaboAnalyst platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://new.metaboanalyst.ca/MetaboAnalyst/home.xhtml\u003c/span\u003e\u003cspan address=\"https://new.metaboanalyst.ca/MetaboAnalyst/home.xhtml\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eGraphPad Prism version 8 (GraphPad Software, Inc.) was used for statistical analysis. Comparisons between two groups were analyzed using two-tailed Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test. Comparisons among multiple groups were analyzed by one-way ANOVA followed by Dunnett\u0026rsquo;s post hoc test. Data are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM of biological replicates. \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eSimulated microgravity alters morphology, mitochondrial ultrastructure, and ROS levels in TNBC cells.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo investigate the effect of microgravity on TNBC cells, we exposed TNBC cells SUM159 and MDA-MB-231 to sMG for 1 or 3 days. sMG was generated using the \u0026ldquo;DARC-G\u0026rdquo; desktop RPM, which is composed of a base frame, a supporting frame, an outer frame, and an inner frame that affixed to the outer frame (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). After sMG exposure, most cell detached from the cell culture flask surface and aggregated to form multicellular spheroids that suspended in the culture medium (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb-d). TEM analysis revealed distinct changes in the mitochondrial morphology following sMG exposure. Mitochondria in normal gravity control cells exhibited typical ovoid structures with intact double membranes and well-organized cristae (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee). In contrast, sMG-treated cells displayed pronounced ultrastructural alterations, including mitochondrial swelling, fragmented cristae, loss of matrix density, and membrane discontinuity. Quantitative analysis demonstrated a significant increase in mitochondrial number per cell, cross-sectional area, average length, and Feret ratio (indicative of elongation) in sMG-treated cells compared to control (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ef). Notably, mitochondrial damage severity was attenuated at day 3 relative to day 1, with partial restoration of cristae organization and reduced swelling. Flow cytometry using DCFH-DA staining revealed elevated ROS levels in sMG-treated SUM159 and MDA-MB-231 cells compared to control, as reflected by increased mean fluorescence intensity (MFI) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eg and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eh). Taken together, these data demonstrate that sMG induces profound morphological alteration, mitochondrial damage, and ROS accumulation in TNBC cells\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSimulated microgravity triggers gene expression profile associated with cellular hypoxic response.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe next examined how microgravity influences gene expression in TNBC cells. SUM159 and MDA-MB-231 cells were cultured under control or sMG conditions for 1 or 3 days, and transcriptomic analysis was performed by RNA sequencing (RNA-seq). In SUM159 cells, compared with control group, we identified a total of 3,228 differentially expressed genes (DEGs) in cells exposed to sMG for 1 day. Among these, 1,744 genes were upregulated and 1,484 genes were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). In MDA-MB-231 cells, a total of 2,930 DEGs were identified after 1-day sMG exposure, with 1,607 genes upregulated and 1,323 genes downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Gene Ontology (GO) enrichment analysis of the common 1,050 DEGs in both cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec) revealed a significant enrichment of GO terms associated with hypoxic response and metabolic processes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee). In addition, gene set enrichment analysis (GSEA) of BioCarta and KEGG pathways demonstrated that cells exposed to 1-day sMG exhibited higher expression levels of genes associated with hypoxia pathway compared to cells in control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe also analyzed RNA-seq results of cells exposed to sMG for 3 days. In SUM159 cells, a total of 2,438 genes were upregulated and 5,245 genes were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eh), and in MDA-MB-231 cells, a total of 1,649 genes were upregulated and 1,109 genes were downregulated, with 3-day sMG exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ei). GO enrichment analysis of the common 1,704 DEGs in SUM159 and MDA-MB-231 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ej) revealed that pathways related to hypoxic response and metabolic processes were also enriched after 3-day sMG exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ek and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003el). Consistently, GSEA confirmed significant enrichment of hypoxia pathway in 3-day sMG-exposed TNBC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003em and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003en). Taken together, these data demonstrate that sMG mediates changes of gene expression that are associated with cellular hypoxic response in TNBC.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSimulated microgravity increases HIF-1α protein level and promotes HIF-1 target genes expression.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eOur transcriptome data suggested that sMG induces a hypoxia-like (pseudohypoxic) response despite normal oxygen levels. Therefore, we hypothesized that sMG might activate HIF-1 and its downstream targets. To test this hypothesis, we referenced two hypoxia-related gene sets from the literature\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, and assessed the expression profile of these genes under sMG in our RNA-seq data. We found that hypoxia-related genes were induced by 3-day exposure to sMG in both cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). We next examined the mRNA levels of several classical HIF-1 target genes, including \u003cem\u003eNDRG1, BNIP3, PDK1, CD73, CD47\u003c/em\u003e and \u003cem\u003eANGPTL4\u003c/em\u003e, under sMG conditions, and found that 3-day sMG exposure increased the expression of most of HIF-1 target genes in both cell lines (with the exception of \u003cem\u003eCD47\u003c/em\u003e in MDA-MB-231) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed). In agreement with the transcriptional data, sMG exposure also increased HIF-1α protein levels in both cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ee).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo determine whether the effects observed under sMG are attributable to microgravity itself rather than simply three-dimensional culture conditions, we performed parallel experiments by culturing cells as adherent monolayers or as mammospheres under normal gravity. Representative images confirmed the formation of distinct mammospheres in both SUM159 and MDA-MB-231 cell lines under normal gravity culture (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ef). We then quantified the mRNA expression of HIF-1A and its canonical target genes by qPCR. Interestingly, mammosphere formation under normal gravity was associated with a significant decrease in the expression of HIF-1A and most of its downstream targets compared with adherent cells in both cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eg and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eh). These results demonstrate that the upregulation of HIF-1 signaling observed under sMG is not a generic consequence of three-dimensional culture. Rather, the induction of HIF-1α and its target genes is a specific response to microgravity exposure. Taken together, these data demonstrate that sMG activates HIF-1 signaling and establishes a pseudohypoxic transcriptional state in TNBC cells.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSimulated microgravity suppresses MYC and its target genes.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe next investigated the effects of sMG on MYC signaling in TNBC cells. RNA-seq analyses revealed a marked and consistent downregulation of multiple MYC target genes in both SUM159 and MDA-MB-231 cells after 1 and 3 days of sMG exposure, relative to normal gravity control (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). To validate these findings, we performed RT-qPCR for mRNA levels of MYC and several representative downstream targets, including \u003cem\u003eASCT2, SRM, AIMP2\u003c/em\u003e, and \u003cem\u003eDKC1\u003c/em\u003e\u003csup\u003e18,19\u003c/sup\u003e. Consistent with the RNA-seq data, sMG exposure for 1 or 3 days significantly decreased mRNA levels of MYC and its target genes in SUM159 and MDA-MB-231 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ed). Western blot analysis further confirmed that c-MYC protein levels were decreased after sMG exposure for 1 or 3 days in both cell lines (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee). Taken together, these data demonstrate that sMG suppresses MYC expression at both mRNA and protein levels, and downregulates the MYC transcriptional program in TNBC cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eHIF-1 is required for sMG-induced pseudohypoxic response and MYC suppression.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eHIF-1 is the master regulator of cellular response to hypoxia\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e.To determine whether HIF-1 is necessary for the pseudohypoxic gene response induced by sMG, we generated stable HIF-1α knockdown and non-targeting control (NTC) subclones in SUM159 and MDA-MB-231 cells. In NTC subclones, sMG exposure for 1 or 3 days significantly increased mRNA levels of classical hypoxia-response genes, such as \u003cem\u003ePDK1\u003c/em\u003e and \u003cem\u003eALDOA\u003c/em\u003e, but decreased mRNA level of \u003cem\u003eMYC\u003c/em\u003e. These sMG-mediated changes were dramatically attenuated in HIF-1α knockdown subclones (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb). Consistently, sMG treatment markedly increased HIF-1α, BNIP3, and LDHA protein levels, and decreased c-MYC protein levels, in NTC cells. HIF-1α knockdown not only abrogated sMG-mediated upregulation of BNIP3 and LDHA, but also partially reversed sMG-mediated suppression of c-MYC (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ec and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ed). These results indicate that HIF-1 is required for sMG-induced pseudohypoxic gene expression and for sMG-driven c-MYC repression.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSimulated microgravity drives metabolic reprogramming in TNBC cells.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eFinally, we examined whether sMG alters metabolic phenotype in TNBC cells. Metabolomic profiling was performed on cell culture supernatants from SUM159 and MDA-MB-231 cells after 1 or 3 days of sMG exposure. Using a cutoff of \u0026gt;\u0026thinsp;1.5-fold increase or \u0026lt;\u0026thinsp;0.8-fold decrease, we identified metabolites that were changed by sMG. A Venn diagram analysis of differentially regulated metabolites in SUM159 and MDA-MB-231 cells at day 1 and day 3 of sMG exposure identified a set of common changing metabolites (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea). KEGG pathway analysis of these common differential metabolites in SUM159 and MDA-MB-231 cells showed significant enrichment in pathways associated with the TCA cycle, glycolysis, glutathione metabolism, and amino acid metabolism, with a largely consistent metabolic profile at both day 1 and day 3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo further explore sMG-induced metabolic changes, we examined expression of genes involved in glycolysis, glutaminolysis, and the TCA cycle\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Heatmaps of RNA-seq data demonstrated a robust upregulation of glycolytic genes, whereas the majority of genes involved in glutaminolysis and the TCA cycle were downregulated after 3 days of sMG exposure (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec-h). These transcriptomic findings were validated by RT-qPCR, which confirmed the induction of key glycolytic genes, including \u003cem\u003eALDOA\u003c/em\u003e, \u003cem\u003eTPI1\u003c/em\u003e, \u003cem\u003eGAPDH\u003c/em\u003e, \u003cem\u003ePKM\u003c/em\u003e, and \u003cem\u003eLDHA\u003c/em\u003e, after sMG exposure for 3 days (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ei). Taken together, these data indicate that sMG drives metabolic reprogramming in TNBC cells, characterized by enhanced glycolysis and suppressed oxidative metabolism.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTNBC is the most aggressive subtype of breast cancer with limited targeted treatment options and a high propensity for metastasis. There is a continuous pursuit of more effective treatment strategies for TNBC\u003csup\u003e\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. In this study, we have demonstrated that sMG induces a coordinated cellular program in TNBC cells that includes morphological remodeling, mitochondrial perturbation, ROS accumulation, and a transcriptional switch towards a HIF-1-dependent pseudohypoxic and glycolytic state. These observations support a model in which altered gravitational signals are transduced into metabolic control through the HIF‑1/c‑MYC axis.\u003c/p\u003e \u003cp\u003ePrevious studies have reported that real or simulated microgravity induces notable morphologic changes in various cell types, such as osteoblasts\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Consistent with those findings, we have observed that most TNBC cells aggregate into multicellular spheroids and suspend in the culture medium when exposed to sMG. This phenomenon is supported by established 3D culture models\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e and has been highlighted as a key area of investigation in breast cancer research under microgravity\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In addition to morphological changes, we have observed that mitochondria, which are central to metabolism and redox homeostasis\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e and whose dynamics are recognized as a therapeutic target in TNBC\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, are particularly sensitive to microgravity. Remarkably, the extent of mitochondrial damage is alleviated after prolonged sMG exposure, as evidenced by partial cristae restoration, suggesting mitochondrial plasticity and adaptive quality control mechanisms\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Such adaptation likely supports cell survival under sustained stress by promoting metabolic reprogramming toward glycolysis\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e and limiting excessive ROS production. These findings underscore the dynamic organellar responses and cellular plasticity of TNBC cells under microgravity, highlighting mitochondria as critical mediators of adaptation to altered gravitational environments.\u003c/p\u003e \u003cp\u003eTranscriptomic analysis have revealed a pseudohypoxic gene expression pattern in TNBC cells under sMG conditions. Specifically, sMG triggers metabolic reprogramming in TNBC cells, characterized by upregulation of glycolysis-related gene and downregulation of TCA cycle-related genes in a HIF-1-dependent manner. This highlights the well-established role of HIF-1 in promoting glycolytic flux while suppressing mitochondrial respiration\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Furthermore, the repression of c-MYC-driven oxidative metabolism and glutaminolysis highlights the well-established antagonistic relationship between HIF-1 and c-MYC in regulating metabolic pathways\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. These findings highlight the critical role of HIF-1 in sensing gravity signals and orchestrating transcriptional reprogramming and three-dimensional growth of TNBC cells in response to sMG, even in the presence of adequate oxygen. Further analysis of transcriptional networks under sMG conditions indicates that hypoxia-related pathways are significantly enriched, alongside increased protein levels of the HIF-1α subunit. These transcriptomic changes contribute to a metabolic shift that appears to prioritize glycolysis over mitochondrial oxidative metabolism. Moreover, in line with the critical role of HIF-1 in promoting glycolysis in response to sMG, HIF-1 activation also represses c-MYC-driven oxidative metabolism and glutaminolysis, further potentiating the glycolytic phenotype. This discovery demonstrates a novel role of HIF-1 as a key regulator in the cellular response to changes of gravity, expanding our understanding of this important transcription factor beyond its traditional function as an oxygen sensor.\u003c/p\u003e \u003cp\u003eAlthough RPM devices are widely used to simulate microgravity environment, residual accelerations, fluid dynamics, and shear stress can influence cellular behavior\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. In our experiments, to reduce fluid shear, cells were cultured in the flasks fully filled with medium for both sMG and normal gravity controls. Importantly, three-dimensional mammosphere growth at normal gravity did not recapitulate HIF-1 activation, indicating that our observations reflect gravity perturbation rather than three-dimensional culture per se. This distinction is supported by studies showing the unique physiological properties of microgravity-induced 3D constructs\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. However, quantitative characterization of residual gravity and shear stress in our setup, inclusion of hardware rotation controls, and direct measurements of intracellular oxygen tension and prolyl-hydroxylase activity\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e would further strengthen causal link between microgravity and the observed cellular responses. Additional TNBC models and in vivo validation studies, including spaceflight or partial‑gravity analogs, are warranted to generalize these findings\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn conclusion, our data demonstrate a gravity‑responsive HIF‑1/c‑MYC module as a central regulator of the metabolic state in TNBC (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). These findings expand the role of HIF‑1 from an oxygen sensor to a gravity‑responsive node that coordinates transcriptional and metabolic adaptation. By coupling biophysical perturbation with targeted metabolic therapy, our work suggests new opportunities to exploit the vulnerabilities of TNBC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\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\u003eAll data and materials are available under the requirement to the corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by National Natural Science Foundation of China (Overseas Excellent Young Scientist Fund Program to H.L.; 82473126 to H.L.), Natural Science Foundation of Shandong Province (ZR2021YQ50 to H.L.;\u0026nbsp;ZR2022QC212\u0026nbsp;to G.J.), Cutting Edge Development Fund of Advanced Medical Research Institute at Shandong University (GYY2023QY01 to H.L.), and Instrument Development Project of Shandong University (zy20250302 to H.L.).Haiquan Lu is a Taishan Scholar Young Talent Professor of Shandong Province and Distinguished Young Professor at Shandong University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eG.J. and H.L. designed the research study. G.J. and Z.Z. performed the experiments and acquired data, H.X. and Z.Z. performed statistical analyses. G.J., Z.Z. and H.L. analyzed the data and wrote the manuscript. H.L. supervised the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Translational Medicine Core Facility of Shandong University for consultation and instrument availability that supported this work.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung, H. et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. \u003cem\u003eCA Cancer J. Clin\u003c/em\u003e. \u003cstrong\u003e71\u003c/strong\u003e, 209\u0026ndash;249 (2021).\u003c/li\u003e\n\u003cli\u003eCheung, A. M. et al. 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Med.\u003c/em\u003e\u003cstrong\u003e14\u003c/strong\u003e, szaf008 (2025).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"npj-microgravity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjmgrav","sideBox":"Learn more about [npj Microgravity](http://www.nature.com/npjmgrav/)","snPcode":"41526","submissionUrl":"https://submission.springernature.com/new-submission/41526/3","title":"npj Microgravity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Simulated microgravity, Pseudohypoxia, Metabolic reprogramming, Hypoxia-inducible factor 1, Triple-negative breast cancer","lastPublishedDoi":"10.21203/rs.3.rs-7839613/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7839613/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWith the expansion of commercial spaceflight and space exploration, the microgravity environment provides unparalleled opportunities to fight against challenging diseases. Here, we investigate the impact of simulated microgravity (sMG) on the cellular morphology and metabolic state of triple-negative breast cancer (TNBC). TNBC cells (SUM159 and MDA-MB-231) were exposed to sMG (~0.001 g) using a random positioning machine (RPM) for 1 and 3 days. Transcriptome profiling revealed that sMG induces a “pseudohypoxic” state, characterized by altered expression of genes typically associated with hypoxia, even under normoxic conditions. sMG upregulates HIF-1α protein levels and its target gene expression\u003cem\u003e, \u003c/em\u003eand downregulates c-MYC and its target gene expression. In addition, sMG mediates metabolic reprogramming of TNBC cells by upregulating gene expression in glycolysis and downregulating gene expression in glutaminolysis and TCA cycle in a HIF-1-dependent manner. Metabolomic analysis further confirmed activation of glycolytic pathway under sMG. Our findings demonstrate that sMG induces a HIF-1-dependent pseudohypoxic and glycolytic state in TNBC cells and implicate a gravity-responsive HIF-1/c-MYC axis in metabolic control.\u003c/p\u003e","manuscriptTitle":"Simulated microgravity induces HIF-1-dependent pseudohypoxic and glycolytic state in triple- negative breast cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-16 16:22:55","doi":"10.21203/rs.3.rs-7839613/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-12T01:38:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-25T22:52:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-25T06:16:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-16T20:01:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"152470644389679560038307251294704062979","date":"2026-02-12T22:42:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"126226354037378646802667209987430126907","date":"2026-02-12T01:14:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"111733207497870824166916752338411463817","date":"2025-12-24T16:06:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-11T12:05:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-02T04:17:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-20T18:03:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Microgravity","date":"2025-10-12T09:08:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-microgravity","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjmgrav","sideBox":"Learn more about [npj Microgravity](http://www.nature.com/npjmgrav/)","snPcode":"41526","submissionUrl":"https://submission.springernature.com/new-submission/41526/3","title":"npj Microgravity","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65efa120-5538-4d44-b8c4-0ce4f514c8f1","owner":[],"postedDate":"December 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":59624021,"name":"Biological sciences/Cancer"},{"id":59624022,"name":"Biological sciences/Cell biology"},{"id":59624023,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2026-05-04T14:24:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-16 16:22:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7839613","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7839613","identity":"rs-7839613","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}