Efficient identification of new small molecules targeting succinate dehydrogenase in non- small cell lung cancer

Efficient identification of new small molecules targeting succinate dehydrogenase in non- small cell lung 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 Research Article Efficient identification of new small molecules targeting succinate dehydrogenase in non- small cell lung cancer Luis Silva, Nicholas Skiados, Nikitha Murugavel, Nastassja Luna, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4197549/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Lung cancer treatment efficacy remains a challenge due to limited therapeutic targets. Succinate dehydrogenase (SDH) enzyme, a crucial enzyme linking the citric acid cycle and the electron transport chain, is implicated in cancer metabolism. While existing compounds target metabolic diseases in vitro , SDH-targeted therapy for lung cancer remains elusive. Methods We assessed SDH expression levels in non-small cell lung (NSCLC) tissues and cell lines. Leveraging AtomNet® technology for compound identification, coupled with mitochondria- and cell-based enzyme activity assays, we discovered new SDH inhibitors. Using 2D monolayer, 3D organoid culture, and assays for cell viability, migration, mitochondrial reactive oxygen species, oxygen consumption rate, succinate accumulation, and apoptosis, we elucidated their mechanism targeting lung malignancy. Results SDH subunits were found to be overexpressed in NSCLC tissues compared to tumor-adjacent normal tissues. Two new SDH inhibitors were identified from 96 predicted candidates. Cellular thermal shift assay confirmed direct binding of these small molecules to SDH subunits in lung cancer cells. Mechanistically, treatment increased cellular and mitochondrial reactive oxygen species, succinate accumulation, and induced apoptosis by damaging mitochondria and DNA, while modulating SDH protein expression. Functionally, these molecules reduced growth, migration, and 3D organoid formation in lung cancer cell lines in vitro , both short and long term. Conclusions Our SDH inhibitors halt tumor growth and migration by targeting key substrate binding sites, showing superior efficacy over existing treatments. They also modulate SDH protein expression, suggesting a promising dual-targeting strategy for cancer therapy. This study sheds light on SDH function in cancer-related metabolic dysfunction and underscores the potential of SDH modulation as a therapeutic strategy for lung cancer and beyond. SDH small molecule inhibitor reactive oxygen species oxygen consumption rate cell apoptosis non-small cell lung cancer Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Metabolic homeostasis is critical to maintaining normal cell proliferation. Aberrant changes in metabolic enzymes and metabolites cause various diseases including cancer 1 . The succinate dehydrogenase (SDH) enzyme complex is a heterotetrameric, mitochondrial inner membrane-bound protein with constituent roles in both the tricarboxylic acid (TCA) cycle and the electron transport chain. The enzyme consists of four major subunits: SDHA, SDHB, SDHC, and SDHD, in addition to several cofactors necessary for the assembly of the functional complex 2 . In the TCA cycle, SDH catalyzes the reduction of succinate to fumarate, coupling the transfer of electrons from this reaction to the electron transfer chain where ubiquinone is reduced to ubiquinol 3 . Due to the nature of complex interactions as an intermediate between these two distinct metabolic processes, SDH is uniquely positioned as a gatekeeper for the metabolic dysfunction observed in various cancers and genetic diseases. SDHA mutations are associated with neurological disorders due to mitochondrial diseases such as Leigh Syndrome and mitochondrial encephalopathy 4 , 5 . Loss-of-function mutations in SDHB , SDHC , and SDHD correlate with hereditary paraganglioma and pheochromocytoma, renal carcinoma, and gastrointestinal stromal tumor 6 – 8 . Accumulation of succinate is associated with tumor invasiveness and drug resistance 9 , 10 . These findings have supported the classification of SDH as a tumor suppressor and the succinate substrate as an oncometabolite, to which excess accumulation mediates tumorigenesis through inhibition of hypoxia-inducible factor (HIF)-1α prolyl hydroxylase (PHD) 11 , 12 . Under normal oxygen conditions, PHD is known to induce the degradation of HIF-1α. Under elevated levels of cytosolic succinate, PHD is inactivated leading to the activation and stabilization of HIF-1α, which results in the activation of HIF response elements in the genome and induction of a pseudohypoxic state 13 . Succinate accumulation is often attributed to loss of function mutations in one or more subunits comprising the SDH enzyme; whether post-translational modifications or endogenous inhibition of SDH play a role in the enzymatic efficiency of SDH is of major interest to our ongoing research in this area. The four primary subunits of the SDH complex are nuclear encoded, with human SDHA on chromosome 5, SDHB and SDHC on chromosome 1, and SDHD on chromosome 11. The subunits must therefore be transcribed and translocated separately, followed by maturation and assembly into the mitochondrial membrane with the help of several auxiliary cofactors 2 . Interestingly, many disease patients presenting with apparent SDH deficiencies do not harbor any mutations of the SDH subunits 14 . Regulation of the complex through RNA editing, RNA modification, and alternative splicing has been shown to induce differential effects on SDH assembly, maturation, and enzymatic function 2 . Therefore, regulation of the complex can be achieved at multiple levels. Non-small cell lung cancer (NSCLC) is among the most common types of cancer worldwide. Lung cancers also represent the leading cancer-related cause of death 15 . NSCLC and small cell lung cancers pose great difficulty for targeted therapeutic intervention in a clinical setting as patients often present with one or more heterozygous genetic mutations which affect drug response 16 . NSCLC often accrues resistance to standard chemotherapeutic agents; resistance has even been observed to third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors which traditionally represent the frontline standard of treatment 17 . To enhance treatment efficacy and patient outcomes in NSCLC, it is crucial to delve into the metabolic dysfunction driving tumorigenesis. Elucidating the molecular mechanisms behind the transition from healthy to cancerous cells, as well as acquired drug resistance, can shed light on lung cancer’s complexity and aid in developing more effective treatments. Prior studies have demonstrated that inhibiting the SDH complex with the anticancer agent lonidamine induces cell death in melanoma by suppressing the pentose phosphate pathway and elevating reactive oxygen species (ROS) levels 18 – 20 , hinting at the therapeutic potential of disrupting complex II in some cancers. To explore this avenue, the Enamine library, consisting of 2.5 million small molecules, was screened with the AtomNet model to identify small molecules targeting the ubiquinone binding pocket of the SDH complex. Ninety-six top candidates including two blinded internal controls were identified for in vitro screening. Initial screening in isolated mitochondria measured SDH activity in immortalized cells, followed by testing in both immortalized and cancer cell lines. Our findings revealed that 67 out of 96 candidates affected electron transfer in SDH-catalyzed reactions. Subsequently, two compounds exhibiting the most potent inhibitory effects on SDH activity were selected for further investigation. Mechanistic characterization through thermal shift assay revealed that these small molecules directly bind to SDHA and SDHD. Oxygen consumption rate (OCR) measurements in mitochondria verified the disruption of cellular respiration by SDH inhibitors. These lead molecules induced oxidative stress and damage to mitochondria and DNA, triggering apoptotic signaling and reducing cell survival, organoid growth, and cell migration in NSCLC cell lines in vitro . Together, these findings underscore the importance of exploring the role of SDH in NSCLC metabolic dysfunction and identify direct SDH targeting as a promising therapeutic approach. Materials and Methods Cell Culture and Cell Lines Each cell line was maintained in a 5% CO 2 atmosphere at 37 o C. Human lung EGFR -mutant cell lines including HCC827, H3255, H1650, PC-9, PC-9ER (erlotinib resistant), and H1975, human lung KRAS -mutant cell lines including H358, H23, Calu-6, H441, A549 and H460, GFP-labelled H1975 and H358 cells, as well as primary mouse embryonic fibroblasts MEF-wt and MB352, were cultured in Dulbecco’s modified Eagle’s medium (DMEM) (Cat#11995-40, Gibco) with 10% fetal bovine serum (FBS, Cat#F4135, MilliporeSigma), 2 mM L-glutamine and 1% penicillin-streptomycin. Immortalized tracheobronchial epithelial AALE cells (provided by William C. Hahn) were derived as previously described 26 and maintained in SAGM media (Cat#CC-3118, Lonza). Cell line identities were confirmed by short tandem repeat (STR) fingerprinting and all were found negative for mycoplasma using the MycoAler Kit (Lonza). Organoid Formation Assay For the formation of H358-GFP organoids, single-cell suspensions were co-plated with geltrex in 96-well non-treated clear plates (Corning, Cat#351172), followed by adding complete growth media. The complete growth media was advanced DMEM/F12 (Gibco) with glutamax (1x, Gibco), HEPES (1x, Gibco), B27 (1x, Gibco), 5 ng/ml Noggin (Life Technologies), 100 ng/ml fibroblast growth factor 10 (FGF10), 20 ng/ml FGF2, 50 ng/ml epidermal growth factor (EGF), 10 ng/ml platelet-derived growth factor AA (PDGF-AA) (Life Technologies), 10 ng/ml FGF7 (Life Technologies), penicillin–streptomycin (1x, Gibco), 1.25 mM N-acetyl-L-cysteine (NAC), 10 mM nicotinamide, and 10 µM forskolin (Sigma). The organoids were grown for a week and then switched to an antioxidant-free media without NAC. Following 24 hours of incubation, organoids were treated with 3 µM (H358-GFP) of H2/Z14 or C6/Z96 with or without 3 mM NAC for 5 ~ 9 days. The media was changed every three days. Organoids were photographed with the EVOS M5000 microscope. Colony Formation Assay Long-term colony formation assay was performed as described previously 71 , 72 . Briefly, H358 conjugated with GFP cells were plated at a density of 250 cells per well in a 96-well black plate (Cat#08772225, Fisher Scientific) with three replicates per group. H358-GFP cells were treated with titrating concentration from 0 \(\mu\) M to 300 \(\mu\) M of indicated compounds for 14 days. Treatment media was changed every three days. Cell viability was determined by GFP signal intensity using a fluorescence microscope. After 14 days, fluorescence images were taken on a fluorescence microscope (Cat#AMF5000, EVOS FL, Life Technology) and the number of colonies was quantified by ImageJ (Version 1.54d 30 March 2023). Antibodies and Reagents For western blotting, rabbit anti-SDHA antibody (1:1000, Cat#11998S, Cell Signaling Technology), anti-SDHB (1:1000, Cat#10620-1-AP, Proteintech), anti-SDHC (1:1000, Cat#14575-1-AP, Proteintech), anti-SDHD (1:1000, Cat#PA5-34387, Invitrogen), mouse anti-HIF-1α (1:1000, Cat#610959, BD), and mouse anti-NRF2 (1:1000, Cat#sc-365949, clone A-10, Santa Cruz Biotechnology) were used as primary antibodies. Mouse anti-β-actin (1:1000, Cat#sc-47778, clone C4, Santa Cruz), mouse anti-GAPDH (Cat# sc-47724, clone A-10, Santa Cruz), and rabbit anti-TOM20 (translocase of outer mitochondrial membrane 20, Cat#11802-1-AP, Proteintech) 73 were used as loading controls. Goat anti-rabbit (1:1000, Cat#32460, Invitrogen) and goat-anti-mouse (1:1000, Cat#32430, Invitrogen) were used as secondary antibodies. For Immunofluorescence, rabbit anti-p21 Cip 1 antibody (1:200, Cat#2947S, Cell Signaling Technology) and rabbit anti- γ-H 2 AX (1:200, Cat#9718S, Cell Signaling Technology) were used primary antibodies. Goat anti-rabbit IgG with Alexa Fluor 555 (1:200, Cat#A32732, Thermo Fisher Scientific) and goat anti-rabbit IgG conjugated with Alexa Fluor 488 (1:200, Cat#A32731TR, Thermo Fisher Scientific) were used as secondary antibodies. Small Molecules Dimethyloxalylglycine (DMOG, Cat#400091, Calbiochem) 74 , diethyl succinate (DES, Cat#112402, Sigma-Aldrich), dimethyl malonate (DMM, Cat#136441, Sigma-Aldrich) 28 , 75 , and NAC (Cat# 616911, Sigma-Aldrich) were used. All small molecules screened for SDH activity were provided by Atomwise Inc. and purchased from Enamine ( https://enamine.net/ ). Atomwise small molecule identification methodology To determine if a SDH structure was available, a HMMER search was performed on the human sequences of interest. The uniprot IDs P31040 (SDHA_HUMAN), P21912 (SDHB_HUMAN), Q99643 (C560_HUMAN), and O14521 (DHSD_HUMAN) were determined to have a percent similarity of 97.3%, 98.2%, 97.0%, and 93.7% to chains A, B, C, and D of the X-ray crystal structure 4YTP (3.10 Å) from Sus scrofa, respectively 24 . Given the high percent similarity between the sequences of interest and the crystal structure chains, it was determined that 4YTP would be used for the virtual screen. Despite looking for agonists, the screening site was selected based on the inhibitor that was co-solved in 4YTP (Flutolanil) and defined by the following residues: Chain B; P169, W172 & W173; Chain C: I30, W35, M39, S42, I43, R46 & I50; Chain D: V87, D90 & Y91 23, 24 . The virtual high throughput screening of the target, SDH enzyme, was performed using the AtomNet neural network 76 . The screening process to identify small molecules in the binding pocket of the SDH complex was performed as previously described by Hseih et al 77 . Briefly, the binding site of interest from the crystal structure 4YTP was used for the virtual screen by the AtomNet model and screened with approximately 2.5 million small molecules from the ENAMINE instock v200204 library ( https://enamine.net/ ). The results from this screen were filtered using Lipinski's rule of five, the scoring from the AtomNet model, physio-chemical property filters, and manual removal of potential electrophiles 22 . This resulted in 94 compounds that were then experimentally analyzed to determine SDH activity. The chemical identifications of the small molecules were blinded to the researchers. Dimethyl sulfoxide (DMSO) was included as a blinded internal control in place of two small molecules to give a total of 96 compounds that were analyzed. Small Molecule Treatment For detecting HIF-1α and NRF2 protein expression after small molecule treatment, human lung cancer cell line H1975 was plated in six-well plates in complete growth media. After 24 hours, the cells were treated with C6/Z96, H2/Z14, dimethyl malonate (DMM), and diethyl succinate (DES) at 30 µM for four hours in serum-free DMEM. For thermal shift assay, H358 cells were treated with respective small molecules (30 µM) for 15 minutes before cell pellets collection. For immunofluorescence staining for SDHA ~ SDHD, cells were plated at 50,000 per coverslip. Then the cells were treated with each small molecule for six hours at a concentration of 30 µM. After treatment, the cells were permeabilized, fixed, and stained. For the cell-based SDH activity assay, cells were plated at 150,000 cells per well and treated with respective small molecules in serum-free DMEM for four hours. The cytosol and mitochondrial ROS assays were conducted by plating cells at a density of 70,000 cells per coverslip. After incubating the cells in DCFDA or MitoSox reagent, treatment media containing small molecules (0 ~ 10 µM) was added and the cells were incubated for six hours before imaging. This was followed by confocal microscopy to quantify fluorescent signals. For colony formation assay, 250 H358 cells expressing GFP were plated and then treated with small molecules continuously for 14 days before imaging. The media containing small molecules was changed every three days. For organoid formation assay, H358-GFP cells were plated and then treated with 3 µM H2/Z14 or C6/Z96 with or without 3 mM NAC continuously for 5 ~ 9 days before imaging. The media containing small molecules was changed every three days. Thermal Shift Assay H358 cells were plated in a six-well plate and treated with a small molecule (30 µM) for 15 minutes. After treatment, cells were scraped with a cell scraper (Cat#TC7023, CellPro), and the wells were washed with phosphate buffer saline (PBS, Cat#10010023, Gibco) before collection. The cells were then pelleted, and the supernatant was removed to leave approximately 20 µl volume. Next, the cell pellets were resuspended by flicking and heated for three minutes at their respective temperature in a mini dry bath incubator (Four E’s Scientific), followed by a three-minute cooldown. 80 µl of RIPA buffer (Radio Immuno Precipitation Assay buffer, Cat#PI89901, Thermo Fisher Scientific) supplemented with protease and phosphatase inhibitor cocktail (Cat#A32963, Thermo Fisher Scientific) was added to the cells to lyse them. The samples were shaken in a 4°C cold room for two hours, followed by a centrifugation step at 4°C for 40 minutes at 14,000 RPM. The supernatant was collected, and protein quantification was measured before western blotting. Harvesting of Mitochondria AALE cells were plated across twenty 10-cm dishes and grown to 90% confluency (~ 3X10 7 cells). Harvesting of the mitochondria was performed using the Mitochondria Isolation Kit (Cat#89874, Thermo Fisher Scientific) for cultured cells. Cells were pelleted in at ~ 850 x g for two minutes and the supernatant was discarded. Then, 800 µl of Mitochondria Isolation Reagent A was added to the pellet. The tube was vortexed at medium speed for five seconds and incubated on ice for exactly two minutes. 10 µl of Mitochondrial Isolation Reagent B was added afterward. Samples were then vortexed at maximum speed for five seconds followed by incubation on ice for five minutes. Within this five-minute period, the tube was vortexed every minute at a maximum speed. After that, 800 µl of Mitochondria Isolation Reagent C was added and the tube was inverted several times. The sample was then centrifuged at 700 x g for 10 minutes at 4°C and the supernatant was transferred to a fresh 2.0 mL centrifuge tube. The supernatant was centrifuged at 12,000 x g for 15 minutes at 4°C and the supernatant was discarded. The resulting pellet was washed with 500 µl of the Mitochondria Isolation Reagent C and centrifuged at 12,000 x g for five minutes. The supernatant was discarded and then the pellet was frozen at -80°C for storage until it was used for SDH activity measurements. Succinate Dehydrogenase Activity Assay SDH activity quantification was performed as described in the Succinate Dehydrogenase Activity Colorimetric Assay Kit (Cat#K660-100, BioVision). For the mitochondria-based assay, extracted mitochondrial pellet aliquots were stored at -80°C. Each aliquot represents one sample well for SDH activity screening with 5X10 5 cells. Small molecules were tested in duplicate at 10 µM for four hours at 4°C, and SDH activity was compared to the PBS control. The SDH activity was determined following the manufacturer’s protocol, and the samples were read in an Envision plate reader for one hour at 595 nm and 25°C. The values were then transformed to SDH activity by the formula (nmol/min/µL = mU/µl = U/mL) and normalized to SDH Activity per cell for comparison across cell lines. For the cell-based assay, AALE cells were plated across a six-well plate in complete SAGM, and the media was changed to low-bovine serum albumin (BSA) SAGM and incubated for fourteen hours. After this incubation, the media was changed back to complete SAGM. Small molecules were added in triplicates to the six well plates at a concentration of 20 µM for 18 hours. To compare the results between different cell lines, the same shortlisted small molecules were screened in H358 cells. H358 cells were plated across six-well plates in complete DMEM. The media was then changed to DMEM with 2% FBS and 1% penicillin/streptomycin and incubated for three hours. After this incubation, media was then changed back to complete DMEM with 10% FBS. Small molecules were added in triplicates at 20 µM and incubated for 18 hours. The cells were then pelleted and processed downstream for SDH Activity assay. Scatterplots were generated by comparing SDH absolute values and relative quantification (RQ) values on the same graph, accounting for variance between assays that were performed on different days. Succinate Assay A standard curve was prepared as per manufacturer protocol (Cat#ab204718, Abcam). Cell lysate was optimized to fit within the standard curve. 125,000 H1975 cells were plated in a 24-well plate (Cat#353047, Corning) and adhered for 24 hours. Cells were treated with respective SDH modulator small molecules for the specified time. After washing with cold PBS, the cells were harvested by scraping, resuspended in 100 µl of ice-cold assay buffer, homogenized, and then centrifuged at a maximum speed at 4°C for five minutes. The appropriate lysate was mixed with 50 µl of master mix and incubated at 37°C for 30 minutes. The optical density was then measured at 450 nm using an Envision plate reader. The absolute quantity of succinate was quantified using the standard curve. Cell Viability Assay Respective cells were plated at 3,000 cells per well on white opaque 96-well plates (Cat#13485, SPL Life Sciences) (2D monolayer) or non-treated 96-well plates (3D organoid) one day before treatment. The cells were then treated with respective small molecules for 72 hours (2D monolayer) or five to nine days (3D organoid). To measure 2D monolayer and 3D organoid cell viability, the CellTiter-Glo® luminescent cell viability assay kit (Cat#G7570, Promega) and 3D CellTiter-Glo® luminescent cell viability assay kit (Cat#G9681, Promega) were used according to the manufacturer’s instructions, respectively. Wound healing assay H1975-GFP cells were plated at 800,000 cells per well and allowed to adhere for 24 hours in a six-well plate (Cat#353046, Corning). After adherence, a wound with equal widths was manually performed, followed by small molecule treatment for 24 hours across six replicates per group 78 . Images were taken using a fluorescence microscope (Cat#AMF5000, EVOS FL, Life Technology) at 0 and 24 hours after treatment. The wound area was measured using ImageJ (V1.54d 30 March 2023). Western Blotting Western blot was performed as previously described 31 . Briefly, cells were lysed in RIPA buffer (Cat#PI89901, Thermo Fisher Scientific) and protein concentration was normalized using Pierce BCA Protein Assay (Cat#23225, Thermo Fisher Scientific). Samples were combined with NuPAGE LDS Sample Buffer (Cat#NP0007, Invitrogen) and NuPAGE Reducing Agent (Cat#NP0004, Invitrogen) and electrophoresed at 200V for 45 min in NuPAGE MES Running Buffer (Cat#NP0002, Invitrogen). Membrane transfer was performed overnight at 17V, followed by blocking in 5% BSA in TBST. Membranes were incubated in a primary antibody followed by an HRP-conjugated secondary antibody and chemiluminescent detection using Supersignal West PICO (Cat#34580, Thermo Fisher Scientific). Proteins were visualized on Chemilmager system (Biorad). Data was analyzed using Image Lab (V6.0.1, Biorad Laboratories Inc). RNA Extraction and qRT-PCR RNA extraction was performed using mirVana miRNA Isolation Kit (Cat#AM1560, Invitrogen) as described previously 79 . A total of 500 ng RNA each sample was input for the Reverse Transcription reaction to acquire the cDNA. Real-time PCR was performed using TaqMan probes on QuantStudio Real-Time PCR. TaqMan probes (Applied Biosystem) included the following: SDHA -Hs00188166_m1 (Cat#4331182), SDHB -Hs00268117_m1 (Cat#4331182), SDHC -Hs01698067_s1 (Cat#4331182), SDHD -Hs00829723_g1 (Cat#4331182), CASP9 -Hs00962278_m1 (Cat#4453320), CYCS -Hs01588974_g1 (Cat#4453320), and GAPDH-Hs02786624_g1 (Cat#4331182). Immunofluorescence staining Before treatment with small molecules, the cells were plated on a poly-L-lysine-coated coverslip in a 35mm petri dish. To observe the cell cycle and DNA damage proteins (p21 Cip 1 and γ-H 2 AX), the cells were treated with a small molecule at 30 µM for four hours. For visualizing the SDH subunits, the cells were treated with a small molecule at 30 µM for six hours. After treatment, the cells were washed with PBS and fixed with 4% paraformaldehyde for 10 minutes. Cell membrane permeabilization was facilitated with 0.1% Triton X-100 in PBS for another 10 minutes. Blocking was performed with 5% BSA in TRIS buffer saline in Tween 20 (TBS-T) for 30 minutes at room temperature, followed by overnight primary antibody incubation at 4°C. The secondary antibody was incubated with the cells in the dark at 37°C for 45 minutes. The slides were prepared with mounting media containing the nucleus dye DAPI. For co-staining, after incubating with the first primary antibody overnight at 4°C, the cells were allowed to incubate with the secondary antibody conjugated with Alexa Fluor 488 for 45 minutes in the dark at 37°C. Then, the second primary antibody was added and incubated at 37°C, followed by incubation with another fluorescence-emitting secondary antibody conjugated with Alexa Fluor 555. The images were taken under a confocal microscope (Zeiss) and quantified using ImageJ software. The mean of the fluorescent signal intensity was used as a measure to analyze the expression levels. Total Cellular ROS measurement Intracellular ROS expression was determined using the DCFDA/H2DCFDA – Cellular ROS Assay kit (Cat#ab113851, Abcam) and performed following the manufacturer’s protocol for confocal imaging. The cells were treated with 30 µM of the small molecules for six hours and then incubated with 1 µg/ml of Hoechst stain (Cat#62249, Thermo Fisher Scientific) for 10 minutes in the dark. After that, the cells were visualized under a confocal microscope (Zeiss). Each group had six biological replicates, which were quantified using ImageJ software. The mean fluorescent signal intensity was used to analyze the expression levels. Mitochondrial ROS measurement H1975 cells were treated with either 1, 3, or 10 µM of H2/Z14, C6/Z96 or vehicle for six hours. After treatment, the cells were loaded with 500 nM MitoSOX (Cat# M36008, Invitrogen) 80 and incubated at 37°C for 30 minutes. The cells were then rinsed three times with warm HBSS with Calcium and Magnesium buffer and imaged using a confocal microscope. The fluorescence intensity was analyzed using Zen Blue 2012 software (Carl Zeiss AG). Oxygen consumption rate analysis Mitochondrial complexes were inhibited by sequential adding of inhibitors and changes in OCR were measured as previously performed 81 . Briefly, H1975 cells were plated in XF96 cell culture microplates (Seahorse Bioscience) at a density of 45,000 cells/well. The OCR was measured using a Seahorse XF96 Analyzer (Seahorse Bioscience) according to the manufacturer’s protocol. The XFe96 extracellular flux assay kit (Seahorse Bioscience) was calibrated using XF calibrant solution (Seahorse Bioscience) by overnight incubation in a non-CO 2 incubator at 37°C. The XFe96 extracellular flux assay kit was loaded with various inhibitors of mitochondrial electron transfer chain complexes, including oligomycin, FCCP, Rotenone and Antimycin A, using the XF cell mito stress test kit (Seahorse Bioscience). The cells were then incubated with XF Assay medium (Seahorse Bioscience) in a non-CO 2 incubator at 37°C for one hour before recording. OCR values were normalized to the number of cells. Statistical Analyses All experiments were performed in 2 to 24 biological replicates and independently reproduced as indicated in figure captions. Data are presented as the means ± SEM. Unless otherwise stated, statistical significance was determined by a student’s two-tailed t -test by GraphPad Prism (v8.4.3). P < 0.05 was considered statistically significant. Two tailed t -test with Welch’s correction was applied for two samples with unequal variances. For three and more samples that are normally distributed, one-way ANOVA was used for multiple comparisons. To analyze Kaplan-Meier curves and hazard ratios for overall survival in lung adenocarcinoma (TCGA_LUAD) patients, the optimal expression cut-off point, determined by the lowest log-rank p-value and the greatest difference in survival, was employed to categorize patients into high and low SDHA or SDHD expression groups. RESULTS Small Molecules Targeting SDH Regulate Enzyme Activity The conventional perception of SDH as a tumor suppressor has been challenged by evidence indicating that inhibiting SDH can induce tumor cell death 21 . To address this inconsistency, we conducted an analysis of SDH subunit expression in lung cancer tissues using The Cancer Genome Atlas (TCGA) database, focusing on the most aggressive forms of the disease. Our analysis revealed significant upregulation of SDHA (p<0.0001), SDHB (p<0.05), and SDHC (p<0.0001) in adenocarcinoma tissues compared to tumor-adjacent normal lung tissues, with a slight downregulation of SDHD in tumor samples (p<0.05) ( Supplementary Fig. 1a ). Additionally, high expression levels of SDHA (p=0.048) and SDHD (p=0.021) were found to be significantly associated with poorer survival outcomes in lung adenocarcinoma patients ( Supplementary Fig. 1b ). These findings suggest that these SDH subunits may represent potential targets for lung adenocarcinoma treatment. Targeting complex II might provide therapeutic benefit in certain types of cancer, as the multifunctional metabolic role of SDH positions it as a master regulator of tumor cell homeostasis 18 . To explore this possibility, we applied a rational drug design approach beginning with screening of a large chemical compound Enamine library in silico against the SDH substrate binding pocket. Targeting the ubiquinone site could stall electrons and generate reactive oxygen species by converting oxygen to superoxide, leading to cell death 22 . The highest conserved crystal structure thus far published, 4YTP, contains an inhibitor in the ubiquinone binding site of complex II, located at the mitochondrial inner membrane, consisting of chains B, C, and D 23 , 24 ( Fig. 1a ). Therefore, the virtual screen was performed using the AtomNet model at the interface of chains B, C, and D of 4YTP where Flutolanil, the inhibitor, was located ( Fig. 1 b~c ). We identified 94 compounds as small molecule candidates to target the ubiquinone site of SDH ( Fig. 1d ), of which two showed significant inhibitory effects when SDH activity was experimentally determined. To identify small molecule inhibitors, we quantified complex II enzymatic activity corresponding to an amount of reduced 2, 6-dichlorophenolindophenol (DCPIP) due to electron transfer in an in vitro reaction 25 , a common method employed ( Supplementary Fig. 2 ). Small molecules identified through in silico screening were then tested for initial target engagement by measuring SDH activity in isolated mitochondria from immortalized bronchial AALE cells 26 , known for consistently expressing high levels of all four SDH subunits ( Fig. 2a and Supplementary Fig. 3a~b ). This observation is supported by a previous study indicating higher SDH expression levels in bronchial epithelial cells compared to alveolar epithelial cells 27 . Among the hits, most compounds reduced SDH enzyme activity, with the strongest inhibitory effects seen with compounds H2/Z14 and C6/Z96 ( Fig. 2b and Table 1 ). Interestingly, this enzyme-based screening approach also identified several compounds with stimulatory effects on SDH activity, which may be useful for further study in indications where SDH function is compromised. Following the unblinding of small molecule chemical identities, the internal controls (DMSO) showed relatively similar effects on SDH activity as our original quality control, phosphate buffered saline (PBS), supporting the validity of the SDH activity assay for assessment of target engagement. After selecting the two compounds with the most potent inhibitory effects on SDH enzyme activity (H2/Z14 and C6/Z96) ( Table 2 ), secondary screening of SDH activity was carried out in intact live AALE and H358 cells. In H358 cells, H2/Z14 and C6/Z96 significantly reduced SDH activity by 42.2% (p<0.001) and 37.2% (p0.05) ( Fig. 2c ). This data suggests that H2/Z14 and C6/Z96 are more potent SDH inhibitors than DMM. Inhibition of SDH can result in the accumulation of succinate 29 . To test this, we administered small molecules that inhibit SDH and measured the levels of succinate. Our experiments showed that succinate levels increased consistently after four and 22 hours of treatment with 30 mM H2/Z14. Additionally, we found that increasing doses of H2/Z14 (0, 3, 10, to 30 mM) led to a continuous increase in succinate levels after 22 hours ( Fig. 2d ). Similarly, we observed a significant increase in succinate levels 22 hours after administering 30 mM C6/Z96 (p<0.0001), although there was no significant change in succinate levels after four hours. Doses of C6/Z96 ranging from 3, 10 to 30 mM also led to a gradual increase in succinate levels (p<0.0001) ( Fig. 2e ). These results suggest that both H2/Z14 and C6/Z96 are effective in inhibiting SDH enzyme activity, leading to an increase in succinate levels. The cellular thermal shift assay is a method for analyzing direct binding of small molecules to proteins by measuring protein denaturation across an increasing range of temperatures, with the resulting melting temperature (Tm) of the protein being the readout 30 31 . We applied this assay to determine whether H2/Z14 and C6/Z96 bind directly to the SDH subunits. As expected, the positive control DMM treatment resulted in an increase in the Tm of SDHA by 10.9°C in H358 cells (DMSO Tm: 41.2°C, DMM Tm: 52.1°C) ( Fig. 2f ). Small molecules H2/Z14 and C6/Z96, also increased Tm of SDHA by 10.9~11.4°C (H2/Z14 Tm: 52.6°C, C6/Z96 Tm: 57.6°C) ( Fig. 2f ). Similarly, H2/Z14 and C6/Z96 significantly increased Tm of SDHD (DMSO Tm: 46.4°C, H2/Z14 Tm: 55.4°C, C6/Z96 Tm: 50.7°C) ( Fig. 2g ). However, none of H2/Z14, C6/Z96, and DMM significantly affected Tm of SDHB ( Supplementary Fig. 4 ). This data suggests that these SDH modulators directly bind to one or more subunits of SDH and may regulate enzyme activity through an allosteric mechanism. Targeting SDH Induces Mitochondrial ROS in Lung Cancer Cells SDH plays a key role in reducing ubiquinone to ubiquinol, but inhibiting the ubiquinone site at the interface of SDHB, SDHC, and SDHD subunits leads to an increase in ROS 32 . Maintaining redox balance is crucial for cellular function 33, 34 . To determine whether targeting SDH affects redox status, we examined the effect of SDH inhibitors on total cellular ROS levels. Following six hours of treatment, we observed a significant 4.2-fold increase in total cellular ROS levels with H2/Z14 (p<0.0001) and a 2.3-fold increase (p<0.0001) with C6/Z96 ( Supplementary Fig. 5a~c ). To assess if the small molecule-induced ROS is primarily derived from the mitochondria, where the functional SDH complex is localized, we measured mitochondrial ROS levels in H1975 cells following small molecule treatment using immunofluorescence staining with MitoSOX and confocal microscopy 35 . We observed a dose-dependent elevation of mitochondrial ROS in cells treated with H2/Z14 and C6/Z96 at 1, 3, and 10 mM ( Fig. 3a~b ). We also measured the oxygen consumption rate (OCR) 36 after four hours of treatment to determine whether these small molecules affect mitochondrial oxidative phosphorylation, since SDH catalyzes the oxidation of succinate into fumarate in the TCA cycle. The results showed that treatment with H2/Z14 and C6/Z96 at 10 mM significantly reduced basal OCR by 12.2% (p<0.001) and 18.9% (p<0.001), and reduced maximal OCR by 32.0% (p<0.01) and 28.2% (p<0.001), respectively ( Fig. 3c ). These findings suggest that SDH inhibitors induce mitochondrial ROS generation and reduce OCR in cancer cells. In response to increased ROS levels, activated nuclear factor (erythroid-derived-2)-like 2 (NRF2) maintains cellular redox balance by activating genes involved in antioxidative functions that neutralize ROS, regenerate NADPH, metabolize iron and heme, and activate the glutathione pathway 37, 38 . To explore the effects of these compounds on redox signaling, we measured NRF2 and HIF-1α expression in H1975 cells following treatment with SDH modulators, as this cell line exhibited abundant SDH components among all tested cell lines. The results revealed that treatment with H2/Z14 and C6/Z96 did not increase NRF2 expression but induced HIF-1α expression ( Supplementary Fig. 6 ). This suggests that targeting SDH impairs NRF2 upregulation in response to elevated ROS. 3D organoids have become a popular preclinical model for screening anti-cancer drugs in NSCLC 39, 40 . To replicate in vivo conditions, we established 3D organoids using green fluorescence protein (GFP)-labeled H358 cell line and tested the effects of chronic treatment with H2/Z14 and C6/Z96 on organoid growth ( Fig. 3d ). After five days of treatment, both H2/Z14 and C6/Z96 at 3 µM significantly decreased the count in H358-GFP organoids by 29.8% (p<0.01) and 39.5% (p<0.001), respectively ( Fig. 3d ). To determine the ROS-dependency of these effects, we treated organoids with a combination of the small molecules and a commonly used antioxidant, N-acetyl-L-cysteine (NAC) 41, 42 . The addition of 3 mM NAC significantly rescued inhibition of organoid growth by 17.8% (p<0.05) and 29.4% (p<0.05) after H2/Z14 and C6/Z96 treatment, respectively ( Fig. 3e ). These data suggest that SDH inhibitors H2/Z14 and C6/Z96 regulate mitochondrial ROS generation, causing a reduction in tumor organoid growth. SDH Inhibitors Affect SDH Protein Abundance in Cancer Cells Given that defects in any subunit of the SDH complex can result in the formation of an aberrantly assembled complex with altered function 43 , we investigated whether targeting SDH could impact SDH abundance. Analyzing SDH gene expression levels across lung adenocarcinoma (LUAD, n=80) and immortalized lung epithelial and fibroblast cell lines (n=8) from the Human Protein Atlas cell line database, we observed significantly higher SDHA expression levels in LUAD compared to lung cell lines (p<0.001), with no notable changes in SDHB , SDHC , and S DHD ( Fig. 4a) . To further explore the effects of SDH inhibitors on SHA and SDHD protein expression in lung cancer cells, specifically because H2/Z14 and C6/Z96 bind to SDHA and SDHD subunits, we conducted immunofluorescence staining and confocal imaging following treatment in H1975 cells with these small molecules. Our results demonstrated that treatment with H2/Z14 in H1975 cells led to a significant decrease in SDHA (p<0.001) and SDHD (p<0.01) ( Fig. 4b~c ). Conversely, C6/Z96 did not induce significant changes in the expression of any subunits (not shown). These findings collectively suggest that functional inhibition of SDH activity may decrease protein expression in certain SDH subunits, likely by disrupting SDH complex assembly. Consequently, this disruption may impede electron transfer and oxidative reduction in complex II. SDH Inhibitors Dysregulate Lung Cancer Cell Proliferation and Migration To investigate the effects of SDH inhibition on cell viability, H460, H1975, H358, H441, and H3255 cancer cell lines were treated with increasing concentrations of small molecules, and cell viability was determined within three days. Both compounds reduced cancer cell viability in a dose-dependent manner. Compound C6/Z96 drastically reduced cell viability in all tested cell lines, with a major inflexion occurring at 62.5 µM ( Supplementary Fig. 7a ). Next, mouse embryonic fibroblast cell lines MEF-wt (wild type) and MB352 were treated with these small molecules to investigate their effects on primary normal cells. Both H2/Z14 and C6/Z96 showed no significant decrease in cell viability up to 62.5 µM ( Supplementary Fig. 7b ). These data reveal that tumor cells respond to SDH inhibition in a dose-dependent manner. Additionally, SDH inhibitors show minimal toxic to normal cells. To further investigate the chronic response of NSCLC cells to SDH inhibition, we performed a colony formation assay in which H358-GFP cells were treated with increasing concentrations of small molecules (0~300 µM) and imaged after 14 days. At 10 µM concentration, C6/Z96 and H2/Z14 significantly reduced colony numbers by 46.7% (p<0.01) and 52.3% (p0.05) and 300 µM did not display obvious changes in colony formation ( Fig. 5a ). These results suggest that targeting SDH impedes long-term lung tumor growth in vitro . A previous study discovered that succinate accumulation induced by SDH inhibition can increase tumor cell migration 9 . However, high levels of ROS can inhibit tumor cell migration and metastasis 44 . Given that ROS levels increased relatively higher than succinate levels following treatment with H2/Z14 and C6/Z96, we hypothesized that inhibiting SDH would reduce tumor cell migration. To investigate this question, we conducted a wound healing assay using GFP-labelled H1975 cells treated with H2/Z14 and C6/Z96. As expected, treatment with H2/Z14 increased the wound area by 3.4-fold at 3 µM (p<0.001) and 4.8-fold at 30 µM (p<0.001) after 24 hours, and C6/Z96 increased the wound area by 4.8-fold at 3 µM (p<0.001) and 6.2-fold at 30 µM (p<0.0001) compared to the DMSO-treated group ( Fig. 5b ). These findings suggest that inhibiting SDH can significantly reduce cell migration, most likely due to the SDH inhibition-induced ROS. Mitochondria can release ROS into the cytosol, impacting both the nucleus and mitochondria, resulting in DNA and mitochondria membrane damage, ultimately triggering cell apoptosis 45 . To assess whether H2/Z14 and C6/Z96 induced DNA damage, we conducted immunofluorescence staining and confocal microscopy for phosphorylated histone H 2 AX (g-H 2 AX) - an early biomarker for DNA double-strand breaks 46 , and p21 Cip1 - a cell cycle suppressor 47 . We found that treatment with H2/Z14 or C6/Z96 increased p21 Cip1 expression by 1.2-fold and 2.5-fold, respectively (p<0.05 and p<0.0001), after a four-hour treatment ( Fig. 5c ). Additionally, treatment with C6/Z96 induced 1.3-fold increase in g-H 2 AX expression, while no notable change was observed following treatment with H2/Z14 ( Supplementary Fig. 8 ). Furthermore, we examined the effect of these inhibitors on mitochondria membrane damage and cell apoptosis biomarkers by analyzing cytochrome C ( CYCS ) and caspase 9 ( CASP9 ) gene expression 48 . The results showed that both H2/Z14 and C6/Z96 caused a significant increase in CYCS gene expression over time (0, 12, and 48 hours). Additionally, the expression of CASP9 , a downstream effector of CYCS , significantly increased at 48 hours after treatment with both inhibitors ( Fig. 5d ). These findings suggest that SDH inhibitors induce tumor cell apoptosis by causing damage to the mitochondria membrane and DNA, probably through elevated mitochondrial ROS. Together, these newly identified compounds induce apoptosis, significantly reducing NSCLC proliferation, colony formation, cell migration, and 3D organoid growth ( Fig. 6 ). This underscores the promising response of NSCLC cells to SDH inhibition. Discussion We have identified two promising small molecules, H2/Z14 and C6/Z96, using the AtomNet® technology for compound identification with mitochondria- and cell-based enzyme activity assays. These small molecules bind directly to SDH subunits in lung cancer cells and increase cellular and mitochondrial ROS, accumulated succinate, and DNA or mitochondria damage-induced apoptosis in lung cancer cell lines. They also reduce the growth, migration, and organoid formation in lung cancer cell lines. In contrast to tumor suppressors such as TP53 and RB1 which are mutated in multiple types of cancers 49 , 50 , the SDH enzyme complex’s tumor suppressive roles are restricted to a few hereditary cancers, including paragangliomas, pheochromocytomas, and gastrointestinal stromal tumors 6 – 8 , 51 , 52 . In contrast, several types of cancers overexpressing SDH, including ovarian cancer and melanoma cell lines, are sensitive to SDH-targeted therapy 18 , 53 . Furthermore, TCGA data in lung cancer has revealed that the subunits ( SDHA, SDHB, SDHC ) are overexpressed in lung adenocarcinoma compared to tumor-adjacent normal tissues significantly. Additionally, blocking SDH with small molecule inhibitors regulates several features of cancer hallmarks 54 , including reduced clonogenicity, cell proliferation, and cell migration, as well as increased DNA or mitochondria damage and cell apoptosis in NSCLC. These conflicting discoveries indicate that SDH's role as a tumor suppressor or an oncogene might be cell-type and context-dependent. In the future, these compounds might be used to treat NSCLC and other highly expressed or dependent on SDH. Additionally, our SDH inhibitors can prevent lung cancer by treating inflammation diseases that overexpress SDH, such as lung fibrosis, which increases the frequency of developing lung cancer and has a protumor role in tumor initiation 55 , 56 . As mitochondria continue to gain appreciation as mediators of tumorigenesis and drug resistance, efforts have increased to identify druggable mitochondrial targets 57 , 58 . While no ongoing clinical trials currently employ SDH inhibitors for NSCLC treatment, our new SDH modulators are poised to become the first candidates for evaluation in preclinical NSCLC models. These two SDH inhibitors reduce tumor cell growth and migration by blocking two key substrate binding sites within SDH: succinate and ubiquinone binding pockets 2 , 3 . Notably, this approach exhibits more potent inhibition of SDH activity than previously known SDH inhibitors, primarily deployed in treating inflammation diseases 28 . Furthermore, these lead compounds have demonstrated the ability to dysregulate SDH protein expression levels for the first time. This is consistent with the recent concept of destabilization or degradation of the targeted protein by small molecule treatment, especially for intracellular proteins 59 , 60 . This new modality may disrupt intracellular SDH complex assembly and inhibit enzyme activity, suggesting a dual-targeting strategy for cancer treatment. Recently, modifying small molecules by adding a lipophilic cation such as an alkyltriphenylphosphonium moiety dramatically increase their delivery to mitochondria in cancer tissues 61 – 63 . In the future, it will be of interest for further optimization of the two SDH inhibits to enhance their potency at nanomolar levels 64 and effective delivery to mitochondria. Increased levels of ROS can have a significant impact on various aspects of cell function, including damage to mitochondria and DNA. H2/Z14 and C6/Z96 treatments have been shown to induce damage to mitochondria, resulting in cell apoptosis, with increased expression of CYCS and CASP9 . Interestingly, C6/Z96 induces less mitochondrial ROS than H2/Z14 at a higher concentration, yet its effects on cell cycle and DNA damage are more pronounced than those of H2/Z14. This unexpected outcome suggests that other molecules besides mitochondrial ROS may be involved in regulating these effects, which could be worth exploring further in future research. At present, there is no proceeding clinical trial that specifically addressing SDH in lung cancer patients. Nevertheless, our preliminary pre-clinical investigations targeting SDH have yielded promising outcomes. We observed tumor regression in both 2D colony and 3D organoid formation assays, accompanied by a reduction in oxygen consumption. These findings align with existing research demonstrating the reliance of lung tumor growth on oxidative phosphorylation and glycolysis, suggesting these pathways are potential therapeutic targets 65 , 66 . Targeting mitochondria in cancer presents a promising therapeutic avenue to disrupt oxidative phosphorylation. This approach has been employed either independently or in combination with other anticancer therapies 67 , 68 . Additionally, mitochondrial targeting has emerged as a viable strategy to overcome drug resistance, given the dysregulation of mitochondrial function often associated with drug-resistant cancers 69 , 70 . Our strategy, centered on SDH targeting, offers a novel approach to blocking lung tumor growth. It can be used as a standalone intervention or in conjunction with other anticancer therapies to further impede tumor progression. Therefore, our study highlights the potential of targeting SDH as a potential therapeutic strategy for lung cancer treatment. Abbreviations ANOVA = analysis of variance BSA = bovine serum albumin CASP9 = caspase 9 CYCS = cytochrome C DCPIP = 2,6-dichlorophenolindophenol DES = diethyl succinate DMEM = Dulbecco’s modified Eagle’s medium DMM = dimethyl malonate DMOG = dimethyloxalylglycine DMSO = dimethyl sulfoxide EGF = epidermal growth factor EGFR = epidermal growth factor receptor FBS = fetal bovine serum FGF = fibroblast growth factor GFP = green fluorescence protein g-H 2 AX = phosphorylated histone H 2 AX HIF1a = hypoxia-inducible factor 1-alpha LUAD = lung adenocarcinoma MEF-wt = mouse embryonic fibroblast cell lines wild type NAC = N-acetyl-L-cysteine NRF2 = nuclear factor (erythroid-derived-2)-like 2 NSCLC = non-small cell lung cancer OCR = oxygen consumption rate PBS = phosphate buffered saline PC-9ER = PC-9 erlotinib resistant PDGF-AA = platelet-derived growth factor AA PHD = prolyl hydroxylase RIPA = Radio Immuno Precipitation Assay ROS = reactive oxygen species RQ = relative quantification SDH = succinate dehydrogenase SDHA = succinate dehydrogenase A SDHB = succinate dehydrogenase B SDHC = succinate dehydrogenase C SDHD = succinate dehydrogenase D SEM = standard error of the mean STR = short tandem repeat TBS-T = TRIS buffer saline in Tween 20 TCA = tricarboxylic acid cycle TCGA = The Cancer Genome Atlas Tm = melting temperature TOM20 = translocase of outer mitochondrial membrane 20 Declarations Availability of data and materials The results shown in this manuscript were partially based upon data generated by the Lung Cancer Explorer portal (https://lce.biohpc.swmed.edu/lungcancer/ ) and Human Protein Atlas database (https://www.proteinatlas.org/). The genetic mutation status was confirmed by cansar portal (v3.0 beta) (https://cansar.icr.ac.uk/) and cancer Catalogue of Somatic mutations in cancer (http://cancer.sanger.ac.uk/cosmic/sample/overview?id=722040). The data that support the plots within this paper and other finding of this study are available from the corresponding author upon reasonable request. Acknowledgments We thank Drs. Suren Tatulian and Yu Yuan (UCF) and the Zhang lab members for the critical reading and comments on the manuscript. A graphical abstract was created with BioRender.com. Funding This study was supported by the Atomwise Award (A19-053) and UCF (University of Central Florida) Exploratory Research Award (Wen Cai Zhang), and UCF Synergy Scholars Graduate Fellow (Luis Silva). Authors’ contributions LS, NS, WCZ, NM, NL, KC, MKG, SCC, and TEO were responsible for conceptualization, data curation, writing original draft, methodology, visualization, formal data analysis and validation. 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MicroRNA-21 guide and passenger strand regulation of adenylosuccinate lyase-mediated purine metabolism promotes transition to an EGFR-TKI-tolerant persister state. Cancer Gene Therapy 2022 : 1-17. Mukhopadhyay P, Rajesh M, Yoshihiro K, Haskó G, Pacher P. Simple quantitative detection of mitochondrial superoxide production in live cells. Biochem Biophys Res Commun 2007; 358 (1) : 203-8. Tahrir FG, Shanmughapriya S, Ahooyi TM, Knezevic T, Gupta MK, Kontos CD et al. Dysregulation of mitochondrial bioenergetics and quality control by HIV‐1 Tat in cardiomyocytes. Journal of Cellular Physiology 2018; 233 (2) : 748-758. Tables Table 1 Changes of SDH enzyme activities in isolated mitochondria from AALE cells treated with small molecules. The top candidates showing a 15% increase or decrease in enzyme activity were listed. Treatment SDH activity (10 -8 nmole/min/mL) Fold change (relative to PBS treatment) E8 1.38E-08 1.40 H7 1.37E-08 1.18 D8 1.36E-08 1.18 E9 1.35E-08 1.18 C12 1.21E-08 0.84 D2 1.21E-08 0.84 E7 1.20E-08 0.84 B6 1.20E-08 0.83 C2 1.20E-08 0.83 F11 1.19E-08 0.82 H8 1.19E-08 0.82 A8 1.18E-08 0.81 E5 1.18E-08 0.81 A11 1.18E-08 0.81 F5 1.17E-08 0.81 A12 1.17E-08 0.81 H10 1.16E-08 0.81 B12 1.16E-08 0.80 H11 1.16E-08 0.79 H9 1.15E-08 0.78 G11 1.15E-08 0.78 G9 1.14E-08 0.78 E2 1.14E-08 0.77 G5 1.13E-08 0.77 B4 1.13E-08 0.77 A10 1.13E-08 0.75 F3 1.12E-08 0.75 H1 1.12E-08 0.75 C4 1.11E-08 0.74 B1 1.11E-08 0.73 G1 1.10E-08 0.73 E11 1.10E-08 0.72 E3 1.10E-08 0.72 D11 1.09E-08 0.72 A7 1.09E-08 0.71 B11 1.08E-08 0.71 B10 1.08E-08 0.71 F1 1.08E-08 0.71 D12 1.07E-08 0.71 D10 1.07E-08 0.70 D6 1.06E-08 0.70 F6 1.06E-08 0.69 E6 1.05E-08 0.68 A5 1.05E-08 0.68 F9 1.04E-08 0.67 A3 1.04E-08 0.67 G6 1.03E-08 0.67 D4 1.03E-08 0.65 C10 1.02E-08 0.65 H6 1.02E-08 0.65 G3 1.01E-08 0.64 H3 1.00E-08 0.64 E10 9.99E-09 0.64 C3 9.92E-09 0.64 H4 9.85E-09 0.64 C5 9.77E-09 0.63 A9 9.70E-09 0.62 F2 9.62E-09 0.61 C11 9.54E-09 0.60 F4 9.47E-09 0.59 B3 9.39E-09 0.59 D3 9.30E-09 0.59 B5 9.20E-09 0.59 A2 9.07E-09 0.57 G2 8.95E-09 0.55 B2 8.85E-09 0.53 G4 8.79E-09 0.52 B7 8.71E-09 0.52 C6 8.59E-09 0.51 E4 8.44E-09 0.51 H2 7.98E-09 0.46 Table 2 The leading two small molecules and their chemical identification Small Molecule Chemical Formula Simplified Molecular-Input Line-Entry System (SMILES) H2/Z14 C18H20N4O CC1=NC(=NO1)C2CCN(CC2)C=3N=C4C=CC=CC4=CC3C C6/Z96 C16H11ClF3N3O2 CC=1C=CC=C2C(=O)NC(CN3C=C(C=C(Cl)C3=O)C(F)(F)F)=NC12 Additional Declarations No competing interests reported. Supplementary Files SDHSupplementalInformation20240325.docx SupplementaryfilefigS9uncroppedWBimages20240403.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4197549","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":287305885,"identity":"a9f1abe9-6a47-47e7-831b-aa00703628fa","order_by":0,"name":"Luis Silva","email":"","orcid":"","institution":"University of Central Florida","correspondingAuthor":false,"prefix":"","firstName":"Luis","middleName":"","lastName":"Silva","suffix":""},{"id":287305887,"identity":"cc14dc42-c06a-4308-ab62-a67825f54629","order_by":1,"name":"Nicholas Skiados","email":"","orcid":"","institution":"University of Central Florida","correspondingAuthor":false,"prefix":"","firstName":"Nicholas","middleName":"","lastName":"Skiados","suffix":""},{"id":287305889,"identity":"6fbdb11b-280a-4339-b263-82a5e9e7fa68","order_by":2,"name":"Nikitha Murugavel","email":"","orcid":"","institution":"University of Central Florida","correspondingAuthor":false,"prefix":"","firstName":"Nikitha","middleName":"","lastName":"Murugavel","suffix":""},{"id":287305890,"identity":"a624ff5d-104e-4e5a-84ee-b1b6735b49b0","order_by":3,"name":"Nastassja Luna","email":"","orcid":"","institution":"University of Central Florida","correspondingAuthor":false,"prefix":"","firstName":"Nastassja","middleName":"","lastName":"Luna","suffix":""},{"id":287305892,"identity":"2da7188f-514e-4dd7-82eb-6eab1d755cde","order_by":4,"name":"Karen Cover","email":"","orcid":"","institution":"University of Central Florida","correspondingAuthor":false,"prefix":"","firstName":"Karen","middleName":"","lastName":"Cover","suffix":""},{"id":287305894,"identity":"edc47fb5-bce5-42d4-99ce-6f467111e8ef","order_by":5,"name":"Manish K. 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The binding site of interest can be seen in the box with residues seen as sticks and a ligand (seen in white) present to define the site for the AtomNet model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b,c)\u003c/strong\u003e Zoomed-in version (b) and surface representation (c) of the binding site of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(d)\u003c/strong\u003e A diagram showing the workflow overview of screening and selecting small molecules using the AtomNet model.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4197549/v1/cecb3389b6ab4672b18e6317.png"},{"id":54271449,"identity":"0f47c6d2-925a-4549-be34-59ca61c1ba79","added_by":"auto","created_at":"2024-04-08 06:51:22","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":118514,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSmall molecules modulate SDH enzyme activity by direct binding.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a) \u003c/strong\u003eFlow chart demonstrating the small molecule selection process and research design. 94 small molecules targeting SDH and DMSO (n=2) were initially gathered by screening with the AtomNet model. Subsequently, single-blinded screening with mitochondria- and cell-based SDH activity and cell viability assays were performed, and two hit small molecules were shortlisted for additional characterization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b) \u003c/strong\u003ePlot depicting effects of small molecules on absolute and relative SDH enzyme activities in isolated mitochondria from AALE cells. The relative SDH activities of all tested small molecules (x-axis) were normalized to that treated with PBS.\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003eN = 2 replicates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(c) \u003c/strong\u003eRelative\u003cstrong\u003e \u003c/strong\u003equantification of per cell SDH activity modulation by small molecules (H2/Z14, C6/Z96, and DMM) in H358 cells treated at 30~50 mM for four hours. N = 4 replicates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(d, e) \u003c/strong\u003eRelative quantification of intracellular succinate levels in H1975 cells treated either 22 hours in a dose-dependent manner or at 30 mM in a time-dependent manner with small molecules H2/Z14 (d) or C6/Z96 (e). N=3 replicates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(f,g) \u003c/strong\u003eThermal shift assay by western blotting for \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eSDHA (f) and\u003cstrong\u003e \u003c/strong\u003eSDHD (g) in H358 cells treated with or without small molecules H2/Z14, C6/Z96, and DMM at 30 mM for 15 minutes. Melting temperature (Tm) was calculated using nonlinear regression analysis. N\u003cem\u003e \u003c/em\u003e= 3 replicates\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are mean± s.e.m. and were analyzed with Welch’s \u003cem\u003et\u003c/em\u003e-test (c) and one-way ANOVA (d,e).\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e*, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05; **, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01; ***, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001, ****, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, ns, not significant.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4197549/v1/09761fd0c5e6d9cb5330a922.png"},{"id":54271453,"identity":"a500fced-919e-4934-ae2f-058fad006904","added_by":"auto","created_at":"2024-04-08 06:51:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":698637,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eH2/Z14 and C6/Z96 induces mitochondrial ROS generation.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a,b) \u003c/strong\u003eImmunofluorescence staining (a) and quantification (b) for mitochondrial ROS using Mitosox assay after six hours of H2/Z14 and C6/Z96 treatment at 0, 1, 3, and 10 µM. The mean fluorescence was quantified by the Zeiss software and calibrated as 1 in the vehicle-treated group (0 µM). Scale bar, 100 mm\u003cstrong\u003e. \u003c/strong\u003eN=3 replicates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(c) \u003c/strong\u003eH1975 cells were treated with H2/Z14 and C6/Z96 for four hours at 10 µM and then were subjected to subsequent treatments with mitochondrial inhibitors including Oligomycin, FCCP and Rotenone/Antimycin A. The basal and maximal oxygen consumption rates (OCR) were measured and quantified using XF96 Seahorse. N=18-24 replicates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(d,e)\u003c/strong\u003e Fluorescent microscopy and quantification of GFP-labelled H358 organoids treated with H2/Z14 and C6/Z96 at 3 µM with or without 3 mM of N-acetylcysteine (NAC) for five days. Quantification of GFP+ organoids was performed by three independent manual counting. The relative number of GFP+ organoids cultured in antioxidant-free media (-NAC) was calibrated as 1, and the relative number of organoids in other groups was normalized to the control group (-NAC). N = 5 replicates.\u003c/p\u003e\n\u003cp\u003eData are mean ± s.e.m. and were analyzed with one-way ANOVA (b,c) and Brown-Forsythe and Welch ANOVA Dunnett’s T3 multiple comparisons test (e) *, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05; **, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01; ***, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001; ns, not significant.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4197549/v1/e8304444ba930cd804a34377.png"},{"id":54271451,"identity":"883e30de-bbf8-4b45-b3bb-7232ca9e8462","added_by":"auto","created_at":"2024-04-08 06:51:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":731207,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eH2/Z14 and C6/Z96 modulate SDH subunit protein abundance.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a) \u003c/strong\u003eNormalized \u003cem\u003eSDHA\u003c/em\u003e, \u003cem\u003eSDHB\u003c/em\u003e, \u003cem\u003eSDHC\u003c/em\u003e, and \u003cem\u003eSDHD\u003c/em\u003eexpression across human lung adenocarcinoma (LUAD, N=80) and immortalized lung epithelial \u0026amp; fibroblast cell lines (Lung, N=8) from the Human Protein Atlas database. nTPM, normalized transcript per million.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b,c) \u003c/strong\u003eImmunofluorescent staining (b) and quantification (c) for SDHA and SDHD of H1975 cells treated with or without small molecules (H2/Z14 and C6/Z96) at 30 mM for six hours. Cells were co-stained with primary anti- anti-SDHA and anti-SDHD antibodies, followed by secondary IgG conjugated with Alexa Fluor 488 or 555. The cells were then counterstained with DAPI and imaged by confocal microscopy. Scale bar = 20 mm. N = 6 replicates.\u003c/p\u003e\n\u003cp\u003eData are mean ± s.e.m. and were analyzed with Welch’s t-test (a,c). **, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01; ***, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001; ns, not significant.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4197549/v1/7fbe27c56e4bdaa91cbd9d85.png"},{"id":54271454,"identity":"76cd664c-7b12-4782-8779-d0e85fc96b3c","added_by":"auto","created_at":"2024-04-08 06:51:22","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":288598,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eH2/Z14 and C6/Z96 inhibit long-term lung tumor cell growth and migration \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ein vitro\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003e Fluorescent microscopy and quantification of GFP-labelled H358 cells incubated with increasing concentrations of small molecules H2/Z14, C6/Z96 (0, 10, 30 µM), and DMM (0, 10, 300 µM) for 14 days. The relative GFP+ colony number in cells treated with PBS was calibrated as 1. Scale bar, 750 µm. N=3 replicates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b) \u003c/strong\u003eWound healing assay and quantification in H1975-GFP cells treated with H2/Z14, C6/Z96, and PBS\u0026nbsp; at 0, 3, and 30 µM for 24 hours. The wound was performed in equal widths across all replicates and Images were visualized for GFP fluorescence. The wound area was normalized to the PBS treatment group at 0 h and quantified using Image J. N = 6 replicates.\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003ec\u003c/strong\u003e) Immunofluorescence staining and quantification for p21\u003csup\u003eCip1 \u003c/sup\u003ein H1975 cells treated with 30 µM H2/Z14, C6/Z96, or PBS for four hours. The fluorescence intensity in cells treated with PBS was calibrated as 1. Scale bar, 20 µm. N = 3 replicates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(d) \u003c/strong\u003eqRT-PCR analysis of gene expression for \u003cem\u003eCYCS \u003c/em\u003eand\u003cem\u003e CASP9\u003c/em\u003e in H1975 cells after treatment with H2/Z14 and C6/Z96 at 30 µM for 0, 12, and 48 hours. The gene expression was normalized to the 0-hour group. \u003cem\u003eGAPDH\u003c/em\u003e was used as an endogenous control.\u003cem\u003e \u003c/em\u003eN = 3 replicates.\u003c/p\u003e\n\u003cp\u003eData are mean ± s.e.m. and were analyzed with one-way ANOVA (a,b,d) and Welch’s t-test (c). *, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05; **, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01; ***, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001; ****, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4197549/v1/014f424103f616b9450f0067.png"},{"id":54272028,"identity":"9d87c62b-de21-46c1-a5c0-e065d22db218","added_by":"auto","created_at":"2024-04-08 06:59:22","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":212603,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eModels of small molecule inhibitors targeting succinate dehydrogenase in cancer.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe leading SDH small molecule modulators primarily target respiratory complex II (succinate dehydrogenase), inducing the production of mitochondrial reactive oxygen species (ROS), which in turn causes DNA damage and initiates cell apoptosis. Consequently, these actions result in the suppression of various cancer characteristics such as colony formation, organoid growth, and cell migration in non-small cell lung cancer.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4197549/v1/69cbb559dda0ecf7744028fe.png"},{"id":54524794,"identity":"2c92579d-5270-49b1-ab7f-9378a0c1560b","added_by":"auto","created_at":"2024-04-11 19:37:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3201791,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4197549/v1/e7d8db25-67f9-42f6-9583-c8ab09d05079.pdf"},{"id":54271455,"identity":"25545c2b-ed55-45db-9f8c-f370c8a26c51","added_by":"auto","created_at":"2024-04-08 06:51:23","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16993339,"visible":true,"origin":"","legend":"","description":"","filename":"SDHSupplementalInformation20240325.docx","url":"https://assets-eu.researchsquare.com/files/rs-4197549/v1/4a34902e0ec7bb8cbf72f5b6.docx"},{"id":54271456,"identity":"f9e263fa-335b-4d4e-918c-4f599034791b","added_by":"auto","created_at":"2024-04-08 06:51:23","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":21991284,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryfilefigS9uncroppedWBimages20240403.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4197549/v1/2e660f29859ba4a6961bbafc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Efficient identification of new small molecules targeting succinate dehydrogenase in non- small cell lung cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMetabolic homeostasis is critical to maintaining normal cell proliferation. Aberrant changes in metabolic enzymes and metabolites cause various diseases including cancer \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The succinate dehydrogenase (SDH) enzyme complex is a heterotetrameric, mitochondrial inner membrane-bound protein with constituent roles in both the tricarboxylic acid (TCA) cycle and the electron transport chain. The enzyme consists of four major subunits: SDHA, SDHB, SDHC, and SDHD, in addition to several cofactors necessary for the assembly of the functional complex \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. In the TCA cycle, SDH catalyzes the reduction of succinate to fumarate, coupling the transfer of electrons from this reaction to the electron transfer chain where ubiquinone is reduced to ubiquinol \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Due to the nature of complex interactions as an intermediate between these two distinct metabolic processes, SDH is uniquely positioned as a gatekeeper for the metabolic dysfunction observed in various cancers and genetic diseases. \u003cem\u003eSDHA\u003c/em\u003e mutations are associated with neurological disorders due to mitochondrial diseases such as Leigh Syndrome and mitochondrial encephalopathy \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Loss-of-function mutations in \u003cem\u003eSDHB\u003c/em\u003e, \u003cem\u003eSDHC\u003c/em\u003e, and \u003cem\u003eSDHD\u003c/em\u003e correlate with hereditary paraganglioma and pheochromocytoma, renal carcinoma, and gastrointestinal stromal tumor \u003csup\u003e\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Accumulation of succinate is associated with tumor invasiveness and drug resistance \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. These findings have supported the classification of SDH as a tumor suppressor and the succinate substrate as an oncometabolite, to which excess accumulation mediates tumorigenesis through inhibition of hypoxia-inducible factor (HIF)-1α prolyl hydroxylase (PHD) \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Under normal oxygen conditions, PHD is known to induce the degradation of HIF-1α. Under elevated levels of cytosolic succinate, PHD is inactivated leading to the activation and stabilization of HIF-1α, which results in the activation of HIF response elements in the genome and induction of a pseudohypoxic state \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Succinate accumulation is often attributed to loss of function mutations in one or more subunits comprising the SDH enzyme; whether post-translational modifications or endogenous inhibition of SDH play a role in the enzymatic efficiency of SDH is of major interest to our ongoing research in this area.\u003c/p\u003e \u003cp\u003eThe four primary subunits of the SDH complex are nuclear encoded, with human SDHA on chromosome 5, SDHB and SDHC on chromosome 1, and SDHD on chromosome 11. The subunits must therefore be transcribed and translocated separately, followed by maturation and assembly into the mitochondrial membrane with the help of several auxiliary cofactors \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Interestingly, many disease patients presenting with apparent SDH deficiencies do not harbor any mutations of the SDH subunits \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Regulation of the complex through RNA editing, RNA modification, and alternative splicing has been shown to induce differential effects on SDH assembly, maturation, and enzymatic function \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Therefore, regulation of the complex can be achieved at multiple levels.\u003c/p\u003e \u003cp\u003eNon-small cell lung cancer (NSCLC) is among the most common types of cancer worldwide. Lung cancers also represent the leading cancer-related cause of death \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. NSCLC and small cell lung cancers pose great difficulty for targeted therapeutic intervention in a clinical setting as patients often present with one or more heterozygous genetic mutations which affect drug response \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. NSCLC often accrues resistance to standard chemotherapeutic agents; resistance has even been observed to third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors which traditionally represent the frontline standard of treatment \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo enhance treatment efficacy and patient outcomes in NSCLC, it is crucial to delve into the metabolic dysfunction driving tumorigenesis. Elucidating the molecular mechanisms behind the transition from healthy to cancerous cells, as well as acquired drug resistance, can shed light on lung cancer\u0026rsquo;s complexity and aid in developing more effective treatments. Prior studies have demonstrated that inhibiting the SDH complex with the anticancer agent lonidamine induces cell death in melanoma by suppressing the pentose phosphate pathway and elevating reactive oxygen species (ROS) levels \u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, hinting at the therapeutic potential of disrupting complex II in some cancers.\u003c/p\u003e \u003cp\u003eTo explore this avenue, the Enamine library, consisting of 2.5\u0026nbsp;million small molecules, was screened with the AtomNet model to identify small molecules targeting the ubiquinone binding pocket of the SDH complex. Ninety-six top candidates including two blinded internal controls were identified for \u003cem\u003ein vitro\u003c/em\u003e screening. Initial screening in isolated mitochondria measured SDH activity in immortalized cells, followed by testing in both immortalized and cancer cell lines. Our findings revealed that 67 out of 96 candidates affected electron transfer in SDH-catalyzed reactions. Subsequently, two compounds exhibiting the most potent inhibitory effects on SDH activity were selected for further investigation. Mechanistic characterization through thermal shift assay revealed that these small molecules directly bind to SDHA and SDHD. Oxygen consumption rate (OCR) measurements in mitochondria verified the disruption of cellular respiration by SDH inhibitors. These lead molecules induced oxidative stress and damage to mitochondria and DNA, triggering apoptotic signaling and reducing cell survival, organoid growth, and cell migration in NSCLC cell lines \u003cem\u003ein vitro\u003c/em\u003e. Together, these findings underscore the importance of exploring the role of SDH in NSCLC metabolic dysfunction and identify direct SDH targeting as a promising therapeutic approach.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCell Culture and Cell Lines\u003c/h2\u003e \u003cp\u003eEach cell line was maintained in a 5% CO\u003csub\u003e2\u003c/sub\u003e atmosphere at 37\u003csup\u003eo\u003c/sup\u003eC. Human lung \u003cem\u003eEGFR\u003c/em\u003e-mutant cell lines including HCC827, H3255, H1650, PC-9, PC-9ER (erlotinib resistant), and H1975, human lung \u003cem\u003eKRAS\u003c/em\u003e-mutant cell lines including H358, H23, Calu-6, H441, A549 and H460, GFP-labelled H1975 and H358 cells, as well as primary mouse embryonic fibroblasts MEF-wt and MB352, were cultured in Dulbecco\u0026rsquo;s modified Eagle\u0026rsquo;s medium (DMEM) (Cat#11995-40, Gibco) with 10% fetal bovine serum (FBS, Cat#F4135, MilliporeSigma), 2 mM L-glutamine and 1% penicillin-streptomycin. Immortalized tracheobronchial epithelial AALE cells (provided by William C. Hahn) were derived as previously described \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e and maintained in SAGM media (Cat#CC-3118, Lonza). Cell line identities were confirmed by short tandem repeat (STR) fingerprinting and all were found negative for mycoplasma using the MycoAler Kit (Lonza).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eOrganoid Formation Assay\u003c/h2\u003e \u003cp\u003eFor the formation of H358-GFP organoids, single-cell suspensions were co-plated with geltrex in 96-well non-treated clear plates (Corning, Cat#351172), followed by adding complete growth media. The complete growth media was advanced DMEM/F12 (Gibco) with glutamax (1x, Gibco), HEPES (1x, Gibco), B27 (1x, Gibco), 5 ng/ml Noggin (Life Technologies), 100 ng/ml fibroblast growth factor 10 (FGF10), 20 ng/ml FGF2, 50 ng/ml epidermal growth factor (EGF), 10 ng/ml platelet-derived growth factor AA (PDGF-AA) (Life Technologies), 10 ng/ml FGF7 (Life Technologies), penicillin\u0026ndash;streptomycin (1x, Gibco), 1.25 mM N-acetyl-L-cysteine (NAC), 10 mM nicotinamide, and 10 \u0026micro;M forskolin (Sigma). The organoids were grown for a week and then switched to an antioxidant-free media without NAC. Following 24 hours of incubation, organoids were treated with 3 \u0026micro;M (H358-GFP) of H2/Z14 or C6/Z96 with or without 3 mM NAC for 5\u0026thinsp;~\u0026thinsp;9 days. The media was changed every three days. Organoids were photographed with the EVOS M5000 microscope.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eColony Formation Assay\u003c/h2\u003e \u003cp\u003eLong-term colony formation assay was performed as described previously \u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e. Briefly, H358 conjugated with GFP cells were plated at a density of 250 cells per well in a 96-well black plate (Cat#08772225, Fisher Scientific) with three replicates per group. H358-GFP cells were treated with titrating concentration from 0 \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\mu\\)\u003c/span\u003e\u003c/span\u003eM to 300\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\mu\\)\u003c/span\u003e\u003c/span\u003eM of indicated compounds for 14 days. Treatment media was changed every three days. Cell viability was determined by GFP signal intensity using a fluorescence microscope. After 14 days, fluorescence images were taken on a fluorescence microscope (Cat#AMF5000, EVOS FL, Life Technology) and the number of colonies was quantified by ImageJ (Version 1.54d 30 March 2023).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eAntibodies and Reagents\u003c/h2\u003e \u003cp\u003eFor western blotting, rabbit anti-SDHA antibody (1:1000, Cat#11998S, Cell Signaling Technology), anti-SDHB (1:1000, Cat#10620-1-AP, Proteintech), anti-SDHC (1:1000, Cat#14575-1-AP, Proteintech), anti-SDHD (1:1000, Cat#PA5-34387, Invitrogen), mouse anti-HIF-1α (1:1000, Cat#610959, BD), and mouse anti-NRF2 (1:1000, Cat#sc-365949, clone A-10, Santa Cruz Biotechnology) were used as primary antibodies. Mouse anti-β-actin (1:1000, Cat#sc-47778, clone C4, Santa Cruz), mouse anti-GAPDH (Cat# sc-47724, clone A-10, Santa Cruz), and rabbit anti-TOM20 (translocase of outer mitochondrial membrane 20, Cat#11802-1-AP, Proteintech) \u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e were used as loading controls. Goat anti-rabbit (1:1000, Cat#32460, Invitrogen) and goat-anti-mouse (1:1000, Cat#32430, Invitrogen) were used as secondary antibodies.\u003c/p\u003e \u003cp\u003eFor Immunofluorescence, rabbit anti-p21\u003csup\u003eCip\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e antibody (1:200, Cat#2947S, Cell Signaling Technology) and rabbit anti- γ-H\u003csub\u003e2\u003c/sub\u003eAX (1:200, Cat#9718S, Cell Signaling Technology) were used primary antibodies. Goat anti-rabbit IgG with Alexa Fluor 555 (1:200, Cat#A32732, Thermo Fisher Scientific) and goat anti-rabbit IgG conjugated with Alexa Fluor 488 (1:200, Cat#A32731TR, Thermo Fisher Scientific) were used as secondary antibodies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSmall Molecules\u003c/h2\u003e \u003cp\u003eDimethyloxalylglycine (DMOG, Cat#400091, Calbiochem) \u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e, diethyl succinate (DES, Cat#112402, Sigma-Aldrich), dimethyl malonate (DMM, Cat#136441, Sigma-Aldrich) \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e, and NAC (Cat# 616911, Sigma-Aldrich) were used. All small molecules screened for SDH activity were provided by Atomwise Inc. and purchased from Enamine (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://enamine.net/\u003c/span\u003e\u003cspan address=\"https://enamine.net/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAtomwise small molecule identification methodology\u003c/h2\u003e \u003cp\u003eTo determine if a SDH structure was available, a HMMER search was performed on the human sequences of interest. The uniprot IDs P31040 (SDHA_HUMAN), P21912 (SDHB_HUMAN), Q99643 (C560_HUMAN), and O14521 (DHSD_HUMAN) were determined to have a percent similarity of 97.3%, 98.2%, 97.0%, and 93.7% to chains A, B, C, and D of the X-ray crystal structure 4YTP (3.10 \u0026Aring;) from Sus scrofa, respectively \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Given the high percent similarity between the sequences of interest and the crystal structure chains, it was determined that 4YTP would be used for the virtual screen. Despite looking for agonists, the screening site was selected based on the inhibitor that was co-solved in 4YTP (Flutolanil) and defined by the following residues: Chain B; P169, W172 \u0026amp; W173; Chain C: I30, W35, M39, S42, I43, R46 \u0026amp; I50; Chain D: V87, D90 \u0026amp; Y91 \u003csup\u003e23, 24\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe virtual high throughput screening of the target, SDH enzyme, was performed using the AtomNet neural network \u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e. The screening process to identify small molecules in the binding pocket of the SDH complex was performed as previously described by Hseih et al \u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. Briefly, the binding site of interest from the crystal structure 4YTP was used for the virtual screen by the AtomNet model and screened with approximately 2.5\u0026nbsp;million small molecules from the ENAMINE instock v200204 library (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://enamine.net/\u003c/span\u003e\u003cspan address=\"https://enamine.net/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e The results from this screen were filtered using Lipinski's rule of five, the scoring from the AtomNet model, physio-chemical property filters, and manual removal of potential electrophiles \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. This resulted in 94 compounds that were then experimentally analyzed to determine SDH activity. The chemical identifications of the small molecules were blinded to the researchers. Dimethyl sulfoxide (DMSO) was included as a blinded internal control in place of two small molecules to give a total of 96 compounds that were analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSmall Molecule Treatment\u003c/h2\u003e \u003cp\u003eFor detecting HIF-1α and NRF2 protein expression after small molecule treatment, human lung cancer cell line H1975 was plated in six-well plates in complete growth media. After 24 hours, the cells were treated with C6/Z96, H2/Z14, dimethyl malonate (DMM), and diethyl succinate (DES) at 30 \u0026micro;M for four hours in serum-free DMEM. For thermal shift assay, H358 cells were treated with respective small molecules (30 \u0026micro;M) for 15 minutes before cell pellets collection. For immunofluorescence staining for SDHA\u0026thinsp;~\u0026thinsp;SDHD, cells were plated at 50,000 per coverslip. Then the cells were treated with each small molecule for six hours at a concentration of 30 \u0026micro;M. After treatment, the cells were permeabilized, fixed, and stained.\u003c/p\u003e \u003cp\u003eFor the cell-based SDH activity assay, cells were plated at 150,000 cells per well and treated with respective small molecules in serum-free DMEM for four hours. The cytosol and mitochondrial ROS assays were conducted by plating cells at a density of 70,000 cells per coverslip. After incubating the cells in DCFDA or MitoSox reagent, treatment media containing small molecules (0\u0026thinsp;~\u0026thinsp;10 \u0026micro;M) was added and the cells were incubated for six hours before imaging. This was followed by confocal microscopy to quantify fluorescent signals.\u003c/p\u003e \u003cp\u003eFor colony formation assay, 250 H358 cells expressing GFP were plated and then treated with small molecules continuously for 14 days before imaging. The media containing small molecules was changed every three days. For organoid formation assay, H358-GFP cells were plated and then treated with 3 \u0026micro;M H2/Z14 or C6/Z96 with or without 3 mM NAC continuously for 5\u0026thinsp;~\u0026thinsp;9 days before imaging. The media containing small molecules was changed every three days.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eThermal Shift Assay\u003c/h2\u003e \u003cp\u003eH358 cells were plated in a six-well plate and treated with a small molecule (30 \u0026micro;M) for 15 minutes. After treatment, cells were scraped with a cell scraper (Cat#TC7023, CellPro), and the wells were washed with phosphate buffer saline (PBS, Cat#10010023, Gibco) before collection. The cells were then pelleted, and the supernatant was removed to leave approximately 20 \u0026micro;l volume. Next, the cell pellets were resuspended by flicking and heated for three minutes at their respective temperature in a mini dry bath incubator (Four E\u0026rsquo;s Scientific), followed by a three-minute cooldown. 80 \u0026micro;l of RIPA buffer (Radio Immuno Precipitation Assay buffer, Cat#PI89901, Thermo Fisher Scientific) supplemented with protease and phosphatase inhibitor cocktail (Cat#A32963, Thermo Fisher Scientific) was added to the cells to lyse them. The samples were shaken in a 4\u0026deg;C cold room for two hours, followed by a centrifugation step at 4\u0026deg;C for 40 minutes at 14,000 RPM. The supernatant was collected, and protein quantification was measured before western blotting.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eHarvesting of Mitochondria\u003c/h2\u003e \u003cp\u003eAALE cells were plated across twenty 10-cm dishes and grown to 90% confluency (~\u0026thinsp;3X10\u003csup\u003e7\u003c/sup\u003e cells). Harvesting of the mitochondria was performed using the Mitochondria Isolation Kit (Cat#89874, Thermo Fisher Scientific) for cultured cells. Cells were pelleted in at ~\u0026thinsp;850 x \u003cem\u003eg\u003c/em\u003e for two minutes and the supernatant was discarded. Then, 800 \u0026micro;l of Mitochondria Isolation Reagent A was added to the pellet. The tube was vortexed at medium speed for five seconds and incubated on ice for exactly two minutes. 10 \u0026micro;l of Mitochondrial Isolation Reagent B was added afterward. Samples were then vortexed at maximum speed for five seconds followed by incubation on ice for five minutes. Within this five-minute period, the tube was vortexed every minute at a maximum speed. After that, 800 \u0026micro;l of Mitochondria Isolation Reagent C was added and the tube was inverted several times. The sample was then centrifuged at 700 x \u003cem\u003eg\u003c/em\u003e for 10 minutes at 4\u0026deg;C and the supernatant was transferred to a fresh 2.0 mL centrifuge tube. The supernatant was centrifuged at 12,000 x \u003cem\u003eg\u003c/em\u003e for 15 minutes at 4\u0026deg;C and the supernatant was discarded. The resulting pellet was washed with 500 \u0026micro;l of the Mitochondria Isolation Reagent C and centrifuged at 12,000 x \u003cem\u003eg\u003c/em\u003e for five minutes. The supernatant was discarded and then the pellet was frozen at -80\u0026deg;C for storage until it was used for SDH activity measurements.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSuccinate Dehydrogenase Activity Assay\u003c/h2\u003e \u003cp\u003eSDH activity quantification was performed as described in the Succinate Dehydrogenase Activity Colorimetric Assay Kit (Cat#K660-100, BioVision). For the mitochondria-based assay, extracted mitochondrial pellet aliquots were stored at -80\u0026deg;C. Each aliquot represents one sample well for SDH activity screening with 5X10\u003csup\u003e5\u003c/sup\u003e cells. Small molecules were tested in duplicate at 10 \u0026micro;M for four hours at 4\u0026deg;C, and SDH activity was compared to the PBS control. The SDH activity was determined following the manufacturer\u0026rsquo;s protocol, and the samples were read in an Envision plate reader for one hour at 595 nm and 25\u0026deg;C. The values were then transformed to SDH activity by the formula (nmol/min/\u0026micro;L\u0026thinsp;=\u0026thinsp;mU/\u0026micro;l\u0026thinsp;=\u0026thinsp;U/mL) and normalized to SDH Activity per cell for comparison across cell lines. For the cell-based assay, AALE cells were plated across a six-well plate in complete SAGM, and the media was changed to low-bovine serum albumin (BSA) SAGM and incubated for fourteen hours. After this incubation, the media was changed back to complete SAGM. Small molecules were added in triplicates to the six well plates at a concentration of 20 \u0026micro;M for 18 hours. To compare the results between different cell lines, the same shortlisted small molecules were screened in H358 cells. H358 cells were plated across six-well plates in complete DMEM. The media was then changed to DMEM with 2% FBS and 1% penicillin/streptomycin and incubated for three hours. After this incubation, media was then changed back to complete DMEM with 10% FBS. Small molecules were added in triplicates at 20 \u0026micro;M and incubated for 18 hours. The cells were then pelleted and processed downstream for SDH Activity assay. Scatterplots were generated by comparing SDH absolute values and relative quantification (RQ) values on the same graph, accounting for variance between assays that were performed on different days.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eSuccinate Assay\u003c/h2\u003e \u003cp\u003eA standard curve was prepared as per manufacturer protocol (Cat#ab204718, Abcam). Cell lysate was optimized to fit within the standard curve. 125,000 H1975 cells were plated in a 24-well plate (Cat#353047, Corning) and adhered for 24 hours. Cells were treated with respective SDH modulator small molecules for the specified time. After washing with cold PBS, the cells were harvested by scraping, resuspended in 100 \u0026micro;l of ice-cold assay buffer, homogenized, and then centrifuged at a maximum speed at 4\u0026deg;C for five minutes. The appropriate lysate was mixed with 50 \u0026micro;l of master mix and incubated at 37\u0026deg;C for 30 minutes. The optical density was then measured at 450 nm using an Envision plate reader. The absolute quantity of succinate was quantified using the standard curve.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCell Viability Assay\u003c/h2\u003e \u003cp\u003eRespective cells were plated at 3,000 cells per well on white opaque 96-well plates (Cat#13485, SPL Life Sciences) (2D monolayer) or non-treated 96-well plates (3D organoid) one day before treatment. The cells were then treated with respective small molecules for 72 hours (2D monolayer) or five to nine days (3D organoid). To measure 2D monolayer and 3D organoid cell viability, the CellTiter-Glo\u0026reg; luminescent cell viability assay kit (Cat#G7570, Promega) and 3D CellTiter-Glo\u0026reg; luminescent cell viability assay kit (Cat#G9681, Promega) were used according to the manufacturer\u0026rsquo;s instructions, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eWound healing assay\u003c/h2\u003e \u003cp\u003eH1975-GFP cells were plated at 800,000 cells per well and allowed to adhere for 24 hours in a six-well plate (Cat#353046, Corning). After adherence, a wound with equal widths was manually performed, followed by small molecule treatment for 24 hours across six replicates per group \u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e. Images were taken using a fluorescence microscope (Cat#AMF5000, EVOS FL, Life Technology) at 0 and 24 hours after treatment. The wound area was measured using ImageJ (V1.54d 30 March 2023).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eWestern Blotting\u003c/h2\u003e \u003cp\u003eWestern blot was performed as previously described \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Briefly, cells were lysed in RIPA buffer (Cat#PI89901, Thermo Fisher Scientific) and protein concentration was normalized using Pierce BCA Protein Assay (Cat#23225, Thermo Fisher Scientific). Samples were combined with NuPAGE LDS Sample Buffer (Cat#NP0007, Invitrogen) and NuPAGE Reducing Agent (Cat#NP0004, Invitrogen) and electrophoresed at 200V for 45 min in NuPAGE MES Running Buffer (Cat#NP0002, Invitrogen). Membrane transfer was performed overnight at 17V, followed by blocking in 5% BSA in TBST. Membranes were incubated in a primary antibody followed by an HRP-conjugated secondary antibody and chemiluminescent detection using Supersignal West PICO (Cat#34580, Thermo Fisher Scientific). Proteins were visualized on Chemilmager system (Biorad). Data was analyzed using Image Lab (V6.0.1, Biorad Laboratories Inc).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eRNA Extraction and qRT-PCR\u003c/h2\u003e \u003cp\u003eRNA extraction was performed using mirVana miRNA Isolation Kit (Cat#AM1560, Invitrogen) as described previously \u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e. A total of 500 ng RNA each sample was input for the Reverse Transcription reaction to acquire the cDNA. Real-time PCR was performed using TaqMan probes on QuantStudio Real-Time PCR. TaqMan probes (Applied Biosystem) included the following: \u003cem\u003eSDHA\u003c/em\u003e-Hs00188166_m1 (Cat#4331182), \u003cem\u003eSDHB\u003c/em\u003e-Hs00268117_m1 (Cat#4331182), \u003cem\u003eSDHC\u003c/em\u003e-Hs01698067_s1 (Cat#4331182), \u003cem\u003eSDHD\u003c/em\u003e-Hs00829723_g1 (Cat#4331182), \u003cem\u003eCASP9\u003c/em\u003e-Hs00962278_m1 (Cat#4453320), \u003cem\u003eCYCS\u003c/em\u003e-Hs01588974_g1 (Cat#4453320), and \u003cem\u003eGAPDH-Hs02786624_g1\u003c/em\u003e (Cat#4331182).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence staining\u003c/h2\u003e \u003cp\u003eBefore treatment with small molecules, the cells were plated on a poly-L-lysine-coated coverslip in a 35mm petri dish. To observe the cell cycle and DNA damage proteins (p21\u003csup\u003eCip\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e and γ-H\u003csub\u003e2\u003c/sub\u003eAX), the cells were treated with a small molecule at 30 \u0026micro;M for four hours. For visualizing the SDH subunits, the cells were treated with a small molecule at 30 \u0026micro;M for six hours. After treatment, the cells were washed with PBS and fixed with 4% paraformaldehyde for 10 minutes. Cell membrane permeabilization was facilitated with 0.1% Triton X-100 in PBS for another 10 minutes. Blocking was performed with 5% BSA in TRIS buffer saline in Tween 20 (TBS-T) for 30 minutes at room temperature, followed by overnight primary antibody incubation at 4\u0026deg;C. The secondary antibody was incubated with the cells in the dark at 37\u0026deg;C for 45 minutes. The slides were prepared with mounting media containing the nucleus dye DAPI.\u003c/p\u003e \u003cp\u003eFor co-staining, after incubating with the first primary antibody overnight at 4\u0026deg;C, the cells were allowed to incubate with the secondary antibody conjugated with Alexa Fluor 488 for 45 minutes in the dark at 37\u0026deg;C. Then, the second primary antibody was added and incubated at 37\u0026deg;C, followed by incubation with another fluorescence-emitting secondary antibody conjugated with Alexa Fluor 555. The images were taken under a confocal microscope (Zeiss) and quantified using ImageJ software. The mean of the fluorescent signal intensity was used as a measure to analyze the expression levels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eTotal Cellular ROS measurement\u003c/h2\u003e \u003cp\u003eIntracellular ROS expression was determined using the DCFDA/H2DCFDA \u0026ndash; Cellular ROS Assay kit (Cat#ab113851, Abcam) and performed following the manufacturer\u0026rsquo;s protocol for confocal imaging. The cells were treated with 30 \u0026micro;M of the small molecules for six hours and then incubated with 1 \u0026micro;g/ml of Hoechst stain (Cat#62249, Thermo Fisher Scientific) for 10 minutes in the dark. After that, the cells were visualized under a confocal microscope (Zeiss). Each group had six biological replicates, which were quantified using ImageJ software. The mean fluorescent signal intensity was used to analyze the expression levels.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eMitochondrial ROS measurement\u003c/h2\u003e \u003cp\u003eH1975 cells were treated with either 1, 3, or 10 \u0026micro;M of H2/Z14, C6/Z96 or vehicle for six hours. After treatment, the cells were loaded with 500 nM MitoSOX (Cat# M36008, Invitrogen) \u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e and incubated at 37\u0026deg;C for 30 minutes. The cells were then rinsed three times with warm HBSS with Calcium and Magnesium buffer and imaged using a confocal microscope. The fluorescence intensity was analyzed using Zen Blue 2012 software (Carl Zeiss AG).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eOxygen consumption rate analysis\u003c/h2\u003e \u003cp\u003eMitochondrial complexes were inhibited by sequential adding of inhibitors and changes in OCR were measured as previously performed \u003csup\u003e\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. Briefly, H1975 cells were plated in XF96 cell culture microplates (Seahorse Bioscience) at a density of 45,000 cells/well. The OCR was measured using a Seahorse XF96 Analyzer (Seahorse Bioscience) according to the manufacturer\u0026rsquo;s protocol. The XFe96 extracellular flux assay kit (Seahorse Bioscience) was calibrated using XF calibrant solution (Seahorse Bioscience) by overnight incubation in a non-CO\u003csub\u003e2\u003c/sub\u003e incubator at 37\u0026deg;C. The XFe96 extracellular flux assay kit was loaded with various inhibitors of mitochondrial electron transfer chain complexes, including oligomycin, FCCP, Rotenone and Antimycin A, using the XF cell mito stress test kit (Seahorse Bioscience). The cells were then incubated with XF Assay medium (Seahorse Bioscience) in a non-CO\u003csub\u003e2\u003c/sub\u003e incubator at 37\u0026deg;C for one hour before recording. OCR values were normalized to the number of cells.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analyses\u003c/h2\u003e \u003cp\u003eAll experiments were performed in 2 to 24 biological replicates and independently reproduced as indicated in figure captions. Data are presented as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM. Unless otherwise stated, statistical significance was determined by a student\u0026rsquo;s two-tailed \u003cem\u003et\u003c/em\u003e-test by GraphPad Prism (v8.4.3). P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Two tailed \u003cem\u003et\u003c/em\u003e-test with Welch\u0026rsquo;s correction was applied for two samples with unequal variances. For three and more samples that are normally distributed, one-way ANOVA was used for multiple comparisons. To analyze Kaplan-Meier curves and hazard ratios for overall survival in lung adenocarcinoma (TCGA_LUAD) patients, the optimal expression cut-off point, determined by the lowest log-rank p-value and the greatest difference in survival, was employed to categorize patients into high and low \u003cem\u003eSDHA\u003c/em\u003e or \u003cem\u003eSDHD\u003c/em\u003e expression groups.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eSmall Molecules Targeting SDH Regulate Enzyme Activity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe conventional perception of SDH as a tumor suppressor has been challenged by evidence indicating that inhibiting SDH can induce tumor cell death \u003csup\u003e21\u003c/sup\u003e. To address this inconsistency, we conducted an analysis of SDH subunit expression in lung cancer tissues using The Cancer Genome Atlas (TCGA) database, focusing on the most aggressive forms of the disease. Our analysis revealed significant upregulation of \u003cem\u003eSDHA\u003c/em\u003e (p\u0026lt;0.0001), \u003cem\u003eSDHB\u003c/em\u003e (p\u0026lt;0.05), and \u003cem\u003eSDHC\u003c/em\u003e (p\u0026lt;0.0001) in adenocarcinoma tissues compared to tumor-adjacent normal lung tissues, with a slight downregulation of \u003cem\u003eSDHD\u003c/em\u003e in tumor samples (p\u0026lt;0.05) (\u003cstrong\u003eSupplementary Fig. 1a\u003c/strong\u003e). Additionally, high expression levels of \u003cem\u003eSDHA\u003c/em\u003e (p=0.048) and\u003cem\u003e SDHD\u003c/em\u003e (p=0.021) were found to be significantly associated with poorer survival outcomes in lung adenocarcinoma patients (\u003cstrong\u003eSupplementary Fig. 1b\u003c/strong\u003e). These findings suggest that these SDH subunits may represent potential targets for lung adenocarcinoma treatment.\u003c/p\u003e\n\u003cp\u003eTargeting complex II might provide therapeutic benefit in certain types of cancer, as the multifunctional metabolic role of SDH positions it as a master regulator of tumor cell homeostasis \u003csup\u003e18\u003c/sup\u003e. To explore this possibility, we applied a rational drug design approach beginning with screening of a large chemical compound Enamine library \u003cem\u003ein silico\u003c/em\u003e against the SDH substrate binding pocket. Targeting the ubiquinone site could stall electrons and generate reactive oxygen species by converting oxygen to superoxide, leading to cell death \u003csup\u003e22\u003c/sup\u003e. The highest conserved crystal structure thus far published, 4YTP, contains an inhibitor in the ubiquinone binding site of complex II, located at the mitochondrial inner membrane, consisting of chains B, C, and D \u003csup\u003e23\u003c/sup\u003e\u003csup\u003e,\u003c/sup\u003e\u003csup\u003e24\u003c/sup\u003e (\u003cstrong\u003eFig. 1a\u003c/strong\u003e). Therefore, the virtual screen was performed using the AtomNet model at the interface of chains B, C, and D of 4YTP where Flutolanil, the inhibitor, was located (\u003cstrong\u003eFig. 1\u003c/strong\u003e\u003cstrong\u003eb~c\u003c/strong\u003e). We identified 94 compounds as small molecule candidates to target the ubiquinone site of SDH (\u003cstrong\u003eFig. 1d\u003c/strong\u003e), of which two showed significant inhibitory effects when SDH activity was experimentally determined. To identify small molecule inhibitors, we quantified complex II enzymatic activity corresponding to an amount of reduced 2, 6-dichlorophenolindophenol (DCPIP) due to electron transfer in an \u003cem\u003ein vitro\u003c/em\u003e reaction \u003csup\u003e25\u003c/sup\u003e, a common method employed (\u003cstrong\u003eSupplementary Fig. 2\u003c/strong\u003e). Small molecules identified through \u003cem\u003ein silico\u003c/em\u003e screening were then tested for initial target engagement by measuring SDH activity in isolated mitochondria from immortalized bronchial AALE cells \u003csup\u003e26\u003c/sup\u003e, known for consistently expressing high levels of all four SDH subunits (\u003cstrong\u003eFig. 2a and Supplementary Fig. 3a~b\u003c/strong\u003e). This observation is supported by a previous study indicating higher SDH expression levels in bronchial epithelial cells compared to alveolar epithelial cells \u003csup\u003e27\u003c/sup\u003e. Among the hits, most compounds reduced SDH enzyme activity, with the strongest inhibitory effects seen with compounds H2/Z14 and C6/Z96 (\u003cstrong\u003eFig. 2b and Table 1\u003c/strong\u003e). Interestingly, this enzyme-based screening approach also identified several compounds with stimulatory effects on SDH activity, which may be useful for further study in indications where SDH function is compromised. Following the unblinding of small molecule chemical identities, the internal controls (DMSO) showed relatively similar effects on SDH activity as our original quality control, phosphate buffered saline (PBS), supporting the validity of the SDH activity assay for assessment of target engagement. After selecting the two compounds with the most potent inhibitory effects on SDH enzyme activity (H2/Z14 and C6/Z96) (\u003cstrong\u003eTable 2\u003c/strong\u003e), secondary screening of SDH activity was carried out in intact live AALE and H358 cells. In H358 cells, H2/Z14 and C6/Z96 significantly reduced SDH activity by 42.2% (p\u0026lt;0.001) and 37.2% (p\u0026lt;0.05) after four-hour treatment, respectively. However, the known SDH inhibitor dimethyl malonate (DMM) \u003csup\u003e28\u003c/sup\u003e only reduced SDH activity by 13.1% (p\u0026gt;0.05) (\u003cstrong\u003eFig. 2c\u003c/strong\u003e). This data suggests that H2/Z14 and C6/Z96 are more potent SDH inhibitors than DMM. \u003c/p\u003e\n\u003cp\u003eInhibition of SDH can result in the accumulation of succinate \u003csup\u003e29\u003c/sup\u003e. To test this, we administered small molecules that inhibit SDH and measured the levels of succinate. Our experiments showed that succinate levels increased consistently after four and 22 hours of treatment with 30 mM H2/Z14. Additionally, we found that increasing doses of H2/Z14 (0, 3, 10, to 30 mM) led to a continuous increase in succinate levels after 22 hours (\u003cstrong\u003eFig. 2d\u003c/strong\u003e). Similarly, we observed a significant increase in succinate levels 22 hours after administering 30 mM C6/Z96 (p\u0026lt;0.0001), although there was no significant change in succinate levels after four hours. Doses of C6/Z96 ranging from 3, 10 to 30 mM also led to a gradual increase in succinate levels (p\u0026lt;0.0001) (\u003cstrong\u003eFig. 2e\u003c/strong\u003e). These results suggest that both H2/Z14 and C6/Z96 are effective in inhibiting SDH enzyme activity, leading to an increase in succinate levels. \u003c/p\u003e\n\u003cp\u003eThe cellular thermal shift assay is a method for analyzing direct binding of small molecules to proteins by measuring protein denaturation across an increasing range of temperatures, with the resulting melting temperature (Tm) of the protein being the readout \u003csup\u003e30\u003c/sup\u003e \u003csup\u003e31\u003c/sup\u003e. We applied this assay to determine whether H2/Z14 and C6/Z96 bind directly to the SDH subunits. As expected, the positive control DMM treatment resulted in an increase in the Tm of SDHA by 10.9\u0026deg;C in H358 cells (DMSO Tm: 41.2\u0026deg;C, DMM Tm: 52.1\u0026deg;C) (\u003cstrong\u003eFig. 2f\u003c/strong\u003e). Small molecules H2/Z14 and C6/Z96, also increased Tm of SDHA by 10.9~11.4\u0026deg;C (H2/Z14 Tm: 52.6\u0026deg;C, C6/Z96 Tm: 57.6\u0026deg;C) (\u003cstrong\u003eFig. 2f\u003c/strong\u003e). Similarly, H2/Z14 and C6/Z96 significantly increased Tm of SDHD (DMSO Tm: 46.4\u0026deg;C, H2/Z14 Tm: 55.4\u0026deg;C, C6/Z96 Tm: 50.7\u0026deg;C) (\u003cstrong\u003eFig. 2g\u003c/strong\u003e). However, none of H2/Z14, C6/Z96, and DMM significantly affected Tm of SDHB (\u003cstrong\u003eSupplementary Fig. 4\u003c/strong\u003e). This data suggests that these SDH modulators directly bind to one or more subunits of SDH and may regulate enzyme activity through an allosteric mechanism. \u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTargeting SDH Induces Mitochondrial ROS in Lung Cancer Cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSDH plays a key role in reducing ubiquinone to ubiquinol, but inhibiting the ubiquinone site at the interface of SDHB, SDHC, and SDHD subunits leads to an increase in ROS \u003csup\u003e32\u003c/sup\u003e. Maintaining redox balance is crucial for cellular function \u003csup\u003e33, 34\u003c/sup\u003e. To determine whether targeting SDH affects redox status, we examined the effect of SDH inhibitors on total cellular ROS levels. Following six hours of treatment, we observed a significant 4.2-fold increase in total cellular ROS levels with H2/Z14 (p\u0026lt;0.0001) and a 2.3-fold increase (p\u0026lt;0.0001) with C6/Z96 (\u003cstrong\u003eSupplementary \u003c/strong\u003e\u003cstrong\u003eFig. 5a~c\u003c/strong\u003e). To assess if the small molecule-induced ROS is primarily derived from the mitochondria, where the functional SDH complex is localized, we measured mitochondrial ROS levels in H1975 cells following small molecule treatment using immunofluorescence staining with MitoSOX and confocal microscopy \u003csup\u003e35\u003c/sup\u003e. We observed a dose-dependent elevation of mitochondrial ROS in cells treated with H2/Z14 and C6/Z96 at 1, 3, and 10 mM (\u003cstrong\u003eFig. 3a~b\u003c/strong\u003e). We also measured the oxygen consumption rate (OCR) \u003csup\u003e36\u003c/sup\u003e after four hours of treatment to determine whether these small molecules affect mitochondrial oxidative phosphorylation, since SDH catalyzes the oxidation of succinate into fumarate in the TCA cycle. The results showed that treatment with H2/Z14 and C6/Z96 at 10 mM significantly reduced basal OCR by 12.2% (p\u0026lt;0.001) and 18.9% (p\u0026lt;0.001), and reduced maximal OCR by 32.0% (p\u0026lt;0.01) and 28.2% (p\u0026lt;0.001), respectively (\u003cstrong\u003eFig. 3c\u003c/strong\u003e). These findings suggest that SDH inhibitors induce mitochondrial ROS generation and reduce OCR in cancer cells. \u003c/p\u003e\n\u003cp\u003eIn response to increased ROS levels, activated nuclear factor (erythroid-derived-2)-like 2 (NRF2) maintains cellular redox balance by activating genes involved in antioxidative functions that neutralize ROS, regenerate NADPH, metabolize iron and heme, and activate the glutathione pathway \u003csup\u003e37, 38\u003c/sup\u003e. To explore the effects of these compounds on redox signaling, we measured NRF2 and HIF-1\u0026alpha; expression in H1975 cells following treatment with SDH modulators, as this cell line exhibited abundant SDH components among all tested cell lines. The results revealed that treatment with H2/Z14 and C6/Z96 did not increase NRF2 expression but induced HIF-1\u0026alpha; expression (\u003cstrong\u003eSupplementary Fig. 6\u003c/strong\u003e). This suggests that targeting SDH impairs NRF2 upregulation in response to elevated ROS.\u003c/p\u003e\n\u003cp\u003e3D organoids have become a popular preclinical model for screening anti-cancer drugs in NSCLC \u003csup\u003e39, 40\u003c/sup\u003e. To replicate \u003cem\u003ein vivo\u003c/em\u003e conditions, we established 3D organoids using green fluorescence protein (GFP)-labeled H358 cell line and tested the effects of chronic treatment with H2/Z14 and C6/Z96 on organoid growth (\u003cstrong\u003eFig. 3d\u003c/strong\u003e). After five days of treatment, both H2/Z14 and C6/Z96 at 3 \u0026micro;M significantly decreased the count in H358-GFP organoids by 29.8% (p\u0026lt;0.01) and 39.5% (p\u0026lt;0.001), respectively (\u003cstrong\u003eFig. 3d\u003c/strong\u003e). To determine the ROS-dependency of these effects, we treated organoids with a combination of the small molecules and a commonly used antioxidant, N-acetyl-L-cysteine (NAC) \u003csup\u003e41, 42\u003c/sup\u003e. The addition of 3 mM NAC significantly rescued inhibition of organoid growth by 17.8% (p\u0026lt;0.05) and 29.4% (p\u0026lt;0.05) after H2/Z14 and C6/Z96 treatment, respectively (\u003cstrong\u003eFig. 3e\u003c/strong\u003e). These data suggest that SDH inhibitors H2/Z14 and C6/Z96 regulate mitochondrial ROS generation, causing a reduction in tumor organoid growth.\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSDH Inhibitors Affect SDH Protein Abundance in Cancer Cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGiven that defects in any subunit of the SDH complex can result in the formation of an aberrantly assembled complex with altered function \u003csup\u003e43\u003c/sup\u003e, we investigated whether targeting SDH could impact SDH abundance. Analyzing SDH gene expression levels across lung adenocarcinoma (LUAD, n=80) and immortalized lung epithelial and fibroblast cell lines (n=8) from the Human Protein Atlas cell line database, we observed significantly higher \u003cem\u003eSDHA\u003c/em\u003e expression levels in LUAD compared to lung cell lines (p\u0026lt;0.001), with no notable changes in \u003cem\u003eSDHB\u003c/em\u003e, \u003cem\u003eSDHC\u003c/em\u003e, and S\u003cem\u003eDHD\u003c/em\u003e (\u003cstrong\u003eFig. 4a)\u003c/strong\u003e. \u003c/p\u003e\n\u003cp\u003eTo further explore the effects of SDH inhibitors on SHA and SDHD protein expression in lung cancer cells, specifically because H2/Z14 and C6/Z96 bind to SDHA and SDHD subunits, we conducted immunofluorescence staining and confocal imaging following treatment in H1975 cells with these small molecules. Our results demonstrated that treatment with H2/Z14 in H1975 cells led to a significant decrease in SDHA (p\u0026lt;0.001) and SDHD (p\u0026lt;0.01) (\u003cstrong\u003eFig. 4b~c\u003c/strong\u003e). Conversely, C6/Z96 did not induce significant changes in the expression of any subunits (not shown). \u003c/p\u003e\n\u003cp\u003eThese findings collectively suggest that functional inhibition of SDH activity may decrease protein expression in certain SDH subunits, likely by disrupting SDH complex assembly. Consequently, this disruption may impede electron transfer and oxidative reduction in complex II.\u003c/p\u003e\n\u003cp\u003e\u003cs\u003e \u003c/s\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSDH Inhibitors Dysregulate Lung Cancer Cell Proliferation and Migration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the effects of SDH inhibition on cell viability, H460, H1975, H358, H441, and H3255 cancer cell lines were treated with increasing concentrations of small molecules, and cell viability was determined within three days. Both compounds reduced cancer cell viability in a dose-dependent manner. Compound C6/Z96 drastically reduced cell viability in all tested cell lines, with a major inflexion occurring at 62.5 \u0026micro;M (\u003cstrong\u003eSupplementary Fig. 7a\u003c/strong\u003e). Next, mouse embryonic fibroblast cell lines MEF-wt (wild type) and MB352 were treated with these small molecules to investigate their effects on primary normal cells. Both H2/Z14 and C6/Z96 showed no significant decrease in cell viability up to 62.5 \u0026micro;M (\u003cstrong\u003eSupplementary \u003c/strong\u003e\u003cstrong\u003eFig. 7b\u003c/strong\u003e). These data reveal that tumor cells respond to SDH inhibition in a dose-dependent manner. Additionally, SDH inhibitors show minimal toxic to normal cells.\u003c/p\u003e\n\u003cp\u003eTo further investigate the chronic response of NSCLC cells to SDH inhibition, we performed a colony formation assay in which H358-GFP cells were treated with increasing concentrations of small molecules (0~300 \u0026micro;M) and imaged after 14 days. At 10 \u0026micro;M concentration, C6/Z96 and H2/Z14 significantly reduced colony numbers by 46.7% (p\u0026lt;0.01) and 52.3% (p\u0026lt;0.01), respectively. However, cells treated with DMM at 10 \u0026micro;M (p\u0026gt;0.05) and 300 \u0026micro;M did not display obvious changes in colony formation (\u003cstrong\u003eFig. 5a\u003c/strong\u003e). These results suggest that targeting SDH impedes long-term lung tumor growth \u003cem\u003ein vitro\u003c/em\u003e. \u003c/p\u003e\n\u003cp\u003eA previous study discovered that succinate accumulation induced by SDH inhibition can increase tumor cell migration \u003csup\u003e9\u003c/sup\u003e. However, high levels of ROS can inhibit tumor cell migration and metastasis \u003csup\u003e44\u003c/sup\u003e. Given that ROS levels increased relatively higher than succinate levels following treatment with H2/Z14 and C6/Z96, we hypothesized that inhibiting SDH would reduce tumor cell migration. To investigate this question, we conducted a wound healing assay using GFP-labelled H1975 cells treated with H2/Z14 and C6/Z96. As expected, treatment with H2/Z14 increased the wound area by 3.4-fold at 3 \u0026micro;M (p\u0026lt;0.001) and 4.8-fold at 30 \u0026micro;M (p\u0026lt;0.001) after 24 hours, and C6/Z96 increased the wound area by 4.8-fold at 3 \u0026micro;M (p\u0026lt;0.001) and 6.2-fold at 30 \u0026micro;M (p\u0026lt;0.0001) compared to the DMSO-treated group (\u003cstrong\u003eFig. 5b\u003c/strong\u003e). These findings suggest that inhibiting SDH can significantly reduce cell migration, most likely due to the SDH inhibition-induced ROS.\u003c/p\u003e\n\u003cp\u003eMitochondria can release ROS into the cytosol, impacting both the nucleus and mitochondria, resulting in DNA and mitochondria membrane damage, ultimately triggering cell apoptosis \u003csup\u003e45\u003c/sup\u003e. To assess whether H2/Z14 and C6/Z96 induced DNA damage, we conducted immunofluorescence staining and confocal microscopy for phosphorylated histone H\u003csub\u003e2\u003c/sub\u003eAX (g-H\u003csub\u003e2\u003c/sub\u003eAX) - an early biomarker for DNA double-strand breaks \u003csup\u003e46\u003c/sup\u003e, and p21\u003csup\u003eCip1\u003c/sup\u003e - a cell cycle suppressor \u003csup\u003e47\u003c/sup\u003e. We found that treatment with H2/Z14 or C6/Z96 increased p21\u003csup\u003eCip1\u003c/sup\u003e expression by 1.2-fold and 2.5-fold, respectively (p\u0026lt;0.05 and p\u0026lt;0.0001), after a four-hour treatment (\u003cstrong\u003eFig. 5c\u003c/strong\u003e). Additionally, treatment with C6/Z96 induced 1.3-fold increase in g-H\u003csub\u003e2\u003c/sub\u003eAX expression, while no notable change was observed following treatment with H2/Z14 (\u003cstrong\u003eSupplementary Fig. 8\u003c/strong\u003e). \u003c/p\u003e\n\u003cp\u003eFurthermore, we examined the effect of these inhibitors on mitochondria membrane damage and cell apoptosis biomarkers by analyzing cytochrome C (\u003cem\u003eCYCS\u003c/em\u003e) and caspase 9 (\u003cem\u003eCASP9\u003c/em\u003e) gene expression \u003csup\u003e48\u003c/sup\u003e. The results showed that both H2/Z14 and C6/Z96 caused a significant increase in \u003cem\u003eCYCS\u003c/em\u003e gene expression over time (0, 12, and 48 hours). Additionally, the expression of \u003cem\u003eCASP9\u003c/em\u003e, a downstream effector of \u003cem\u003eCYCS\u003c/em\u003e, significantly increased at 48 hours after treatment with both inhibitors (\u003cstrong\u003eFig. 5d\u003c/strong\u003e). These findings suggest that SDH inhibitors induce tumor cell apoptosis by causing damage to the mitochondria membrane and DNA, probably through elevated mitochondrial ROS. \u003c/p\u003e\n\u003cp\u003eTogether, these newly identified compounds induce apoptosis, significantly reducing NSCLC proliferation, colony formation, cell migration, and 3D organoid growth (\u003cstrong\u003eFig. 6\u003c/strong\u003e). This underscores the promising response of NSCLC cells to SDH inhibition.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe have identified two promising small molecules, H2/Z14 and C6/Z96, using the AtomNet\u0026reg; technology for compound identification with mitochondria- and cell-based enzyme activity assays. These small molecules bind directly to SDH subunits in lung cancer cells and increase cellular and mitochondrial ROS, accumulated succinate, and DNA or mitochondria damage-induced apoptosis in lung cancer cell lines. They also reduce the growth, migration, and organoid formation in lung cancer cell lines. In contrast to tumor suppressors such as \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003eRB1\u003c/em\u003e which are mutated in multiple types of cancers \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e, the SDH enzyme complex\u0026rsquo;s tumor suppressive roles are restricted to a few hereditary cancers, including paragangliomas, pheochromocytomas, and gastrointestinal stromal tumors \u003csup\u003e\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. In contrast, several types of cancers overexpressing SDH, including ovarian cancer and melanoma cell lines, are sensitive to SDH-targeted therapy \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Furthermore, TCGA data in lung cancer has revealed that the subunits (\u003cem\u003eSDHA, SDHB, SDHC\u003c/em\u003e) are overexpressed in lung adenocarcinoma compared to tumor-adjacent normal tissues significantly. Additionally, blocking SDH with small molecule inhibitors regulates several features of cancer hallmarks \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, including reduced clonogenicity, cell proliferation, and cell migration, as well as increased DNA or mitochondria damage and cell apoptosis in NSCLC. These conflicting discoveries indicate that SDH's role as a tumor suppressor or an oncogene might be cell-type and context-dependent. In the future, these compounds might be used to treat NSCLC and other highly expressed or dependent on SDH. Additionally, our SDH inhibitors can prevent lung cancer by treating inflammation diseases that overexpress SDH, such as lung fibrosis, which increases the frequency of developing lung cancer and has a protumor role in tumor initiation \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs mitochondria continue to gain appreciation as mediators of tumorigenesis and drug resistance, efforts have increased to identify druggable mitochondrial targets \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. While no ongoing clinical trials currently employ SDH inhibitors for NSCLC treatment, our new SDH modulators are poised to become the first candidates for evaluation in preclinical NSCLC models. These two SDH inhibitors reduce tumor cell growth and migration by blocking two key substrate binding sites within SDH: succinate and ubiquinone binding pockets \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Notably, this approach exhibits more potent inhibition of SDH activity than previously known SDH inhibitors, primarily deployed in treating inflammation diseases \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Furthermore, these lead compounds have demonstrated the ability to dysregulate SDH protein expression levels for the first time. This is consistent with the recent concept of destabilization or degradation of the targeted protein by small molecule treatment, especially for intracellular proteins \u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. This new modality may disrupt intracellular SDH complex assembly and inhibit enzyme activity, suggesting a dual-targeting strategy for cancer treatment. Recently, modifying small molecules by adding a lipophilic cation such as an alkyltriphenylphosphonium moiety dramatically increase their delivery to mitochondria in cancer tissues \u003csup\u003e\u003cspan additionalcitationids=\"CR62\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. In the future, it will be of interest for further optimization of the two SDH inhibits to enhance their potency at nanomolar levels \u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e and effective delivery to mitochondria.\u003c/p\u003e \u003cp\u003eIncreased levels of ROS can have a significant impact on various aspects of cell function, including damage to mitochondria and DNA. H2/Z14 and C6/Z96 treatments have been shown to induce damage to mitochondria, resulting in cell apoptosis, with increased expression of \u003cem\u003eCYCS\u003c/em\u003e and \u003cem\u003eCASP9\u003c/em\u003e. Interestingly, C6/Z96 induces less mitochondrial ROS than H2/Z14 at a higher concentration, yet its effects on cell cycle and DNA damage are more pronounced than those of H2/Z14. This unexpected outcome suggests that other molecules besides mitochondrial ROS may be involved in regulating these effects, which could be worth exploring further in future research.\u003c/p\u003e \u003cp\u003eAt present, there is no proceeding clinical trial that specifically addressing SDH in lung cancer patients. Nevertheless, our preliminary pre-clinical investigations targeting SDH have yielded promising outcomes. We observed tumor regression in both 2D colony and 3D organoid formation assays, accompanied by a reduction in oxygen consumption. These findings align with existing research demonstrating the reliance of lung tumor growth on oxidative phosphorylation and glycolysis, suggesting these pathways are potential therapeutic targets \u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. Targeting mitochondria in cancer presents a promising therapeutic avenue to disrupt oxidative phosphorylation. This approach has been employed either independently or in combination with other anticancer therapies \u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. Additionally, mitochondrial targeting has emerged as a viable strategy to overcome drug resistance, given the dysregulation of mitochondrial function often associated with drug-resistant cancers \u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. Our strategy, centered on SDH targeting, offers a novel approach to blocking lung tumor growth. It can be used as a standalone intervention or in conjunction with other anticancer therapies to further impede tumor progression.\u003c/p\u003e \u003cp\u003eTherefore, our study highlights the potential of targeting SDH as a potential therapeutic strategy for lung cancer treatment.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eANOVA = analysis of variance\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBSA = bovine serum albumin\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCASP9 = caspase 9\u003c/p\u003e\n\u003cp\u003eCYCS = cytochrome C\u003c/p\u003e\n\u003cp\u003eDCPIP = 2,6-dichlorophenolindophenol\u003c/p\u003e\n\u003cp\u003eDES = diethyl succinate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDMEM = Dulbecco\u0026rsquo;s modified Eagle\u0026rsquo;s medium\u003c/p\u003e\n\u003cp\u003eDMM = dimethyl malonate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDMOG = dimethyloxalylglycine\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDMSO = dimethyl sulfoxide\u003c/p\u003e\n\u003cp\u003eEGF = epidermal growth factor\u003c/p\u003e\n\u003cp\u003eEGFR = epidermal growth factor receptor\u003c/p\u003e\n\u003cp\u003eFBS = fetal bovine serum\u003c/p\u003e\n\u003cp\u003eFGF = fibroblast growth factor\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGFP = green fluorescence protein\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eg-H\u003csub\u003e2\u003c/sub\u003eAX = phosphorylated histone H\u003csub\u003e2\u003c/sub\u003eAX\u003c/p\u003e\n\u003cp\u003eHIF1a\u0026nbsp;= hypoxia-inducible factor 1-alpha\u003c/p\u003e\n\u003cp\u003eLUAD = lung adenocarcinoma\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMEF-wt = mouse embryonic fibroblast cell lines wild type\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNAC = N-acetyl-L-cysteine\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNRF2 = nuclear\u0026nbsp;factor (erythroid-derived-2)-like 2\u003c/p\u003e\n\u003cp\u003eNSCLC = non-small cell lung cancer\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOCR = oxygen consumption rate\u003c/p\u003e\n\u003cp\u003ePBS = phosphate buffered saline\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePC-9ER = PC-9 erlotinib resistant\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePDGF-AA\u0026nbsp;= platelet-derived growth factor AA\u003c/p\u003e\n\u003cp\u003ePHD = prolyl hydroxylase\u003c/p\u003e\n\u003cp\u003eRIPA = Radio Immuno Precipitation Assay\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eROS = reactive oxygen species\u003c/p\u003e\n\u003cp\u003eRQ = relative quantification\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSDH = succinate dehydrogenase\u003c/p\u003e\n\u003cp\u003eSDHA = succinate dehydrogenase A\u003c/p\u003e\n\u003cp\u003eSDHB = succinate dehydrogenase B\u003c/p\u003e\n\u003cp\u003eSDHC = succinate dehydrogenase C\u003c/p\u003e\n\u003cp\u003eSDHD = succinate dehydrogenase D\u003c/p\u003e\n\u003cp\u003eSEM = standard error of the mean\u003c/p\u003e\n\u003cp\u003eSTR = short tandem repeat\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTBS-T\u0026nbsp;= TRIS buffer saline in Tween 20\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTCA = tricarboxylic acid cycle\u003c/p\u003e\n\u003cp\u003eTCGA = The Cancer Genome Atlas\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTm = melting temperature\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTOM20 = translocase of outer mitochondrial membrane 20\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results shown in this manuscript were partially based upon data generated by the Lung Cancer Explorer portal (https://lce.biohpc.swmed.edu/lungcancer/\u003cu\u003e)\u003c/u\u003e and Human Protein Atlas database (https://www.proteinatlas.org/). The genetic mutation status was confirmed by cansar portal (v3.0 beta) (https://cansar.icr.ac.uk/) and cancer Catalogue of Somatic mutations in cancer (http://cancer.sanger.ac.uk/cosmic/sample/overview?id=722040). The data that support the plots within this paper and other finding of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Drs. Suren Tatulian and Yu Yuan (UCF) and the Zhang lab members for the critical reading and comments on the manuscript. A graphical abstract was created with BioRender.com.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Atomwise Award (A19-053) and UCF (University of Central Florida) Exploratory Research Award (Wen Cai Zhang), and UCF Synergy Scholars Graduate Fellow (Luis Silva). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLS, NS, WCZ, NM, NL, KC, MKG, SCC, and TEO were responsible for conceptualization, data curation, writing original draft, methodology, visualization, formal data analysis and validation. LS, NS, and WCZ were responsible for reviewing and editing manuscript. WCZ was responsible for funding acquisition, project administration, resources, and supervision.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot available. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have agreed to publish this manuscript. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eZhu J, Thompson CB. 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The top candidates showing a 15% increase or decrease in enzyme activity were listed.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"93%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eTreatment\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003eSDH activity (10\u003csup\u003e-8\u003c/sup\u003e nmole/min/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003eFold change (relative to PBS treatment)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eE8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.38E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eH7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.37E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eD8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.36E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eE9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.35E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eC12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.21E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eD2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.21E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eE7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.20E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eB6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.20E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eC2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.20E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eF11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.19E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eH8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.19E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eA8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.18E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eE5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.18E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eA11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.18E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eF5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.17E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eA12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.17E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eH10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.16E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eB12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.16E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eH11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.16E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eH9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.15E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eG11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.15E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eG9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.14E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.14E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eG5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.13E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eB4\u003c/p\u003e\n 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valign=\"top\"\u003e\n \u003cp\u003eE3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.10E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eD11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.09E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eA7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.09E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eB11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.08E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eB10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.08E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.08E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eD12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.07E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eD10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.07E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eD6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.06E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eF6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.06E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eE6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.05E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eA5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.05E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eF9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.04E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eA3\u003c/p\u003e\n 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\u003cp\u003e1.01E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eH3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e1.00E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eE10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e9.99E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e9.92E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eH4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e9.85E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eC5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e9.77E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eA9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e9.70E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e9.62E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eC11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e9.54E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e9.47E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eB3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e9.39E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eD3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e9.30E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eB5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e9.20E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eA2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e9.07E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eG2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e8.95E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eB2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e8.85E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eG4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e8.79E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eB7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e8.71E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eC6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e8.59E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eE4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e8.44E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"14.285714285714286%\" valign=\"top\"\u003e\n \u003cp\u003eH2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.83673469387755%\" valign=\"top\"\u003e\n \u003cp\u003e7.98E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.87755102040816%\" valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 The leading two small molecules and their chemical identification\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eSmall Molecule\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.21212121212121%\" valign=\"top\"\u003e\n \u003cp\u003eChemical Formula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"67.67676767676768%\" valign=\"top\"\u003e\n \u003cp\u003eSimplified Molecular-Input Line-Entry System (SMILES)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eH2/Z14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.21212121212121%\" valign=\"top\"\u003e\n \u003cp\u003eC18H20N4O\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"67.67676767676768%\" valign=\"top\"\u003e\n \u003cp\u003eCC1=NC(=NO1)C2CCN(CC2)C=3N=C4C=CC=CC4=CC3C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003eC6/Z96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.21212121212121%\" valign=\"top\"\u003e\n \u003cp\u003eC16H11ClF3N3O2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"67.67676767676768%\" valign=\"top\"\u003e\n \u003cp\u003eCC=1C=CC=C2C(=O)NC(CN3C=C(C=C(Cl)C3=O)C(F)(F)F)=NC12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"SDH, small molecule inhibitor, reactive oxygen species, oxygen consumption rate, cell apoptosis, non-small cell lung cancer","lastPublishedDoi":"10.21203/rs.3.rs-4197549/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4197549/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eLung cancer treatment efficacy remains a challenge due to limited therapeutic targets. Succinate dehydrogenase (SDH) enzyme, a crucial enzyme linking the citric acid cycle and the electron transport chain, is implicated in cancer metabolism. While existing compounds target metabolic diseases \u003cem\u003ein vitro\u003c/em\u003e, SDH-targeted therapy for lung cancer remains elusive.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe assessed SDH expression levels in non-small cell lung (NSCLC) tissues and cell lines. Leveraging AtomNet\u0026reg; technology for compound identification, coupled with mitochondria- and cell-based enzyme activity assays, we discovered new SDH inhibitors. Using 2D monolayer, 3D organoid culture, and assays for cell viability, migration, mitochondrial reactive oxygen species, oxygen consumption rate, succinate accumulation, and apoptosis, we elucidated their mechanism targeting lung malignancy.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSDH subunits were found to be overexpressed in NSCLC tissues compared to tumor-adjacent normal tissues. Two new SDH inhibitors were identified from 96 predicted candidates. Cellular thermal shift assay confirmed direct binding of these small molecules to SDH subunits in lung cancer cells. Mechanistically, treatment increased cellular and mitochondrial reactive oxygen species, succinate accumulation, and induced apoptosis by damaging mitochondria and DNA, while modulating SDH protein expression. Functionally, these molecules reduced growth, migration, and 3D organoid formation in lung cancer cell lines \u003cem\u003ein vitro\u003c/em\u003e, both short and long term.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur SDH inhibitors halt tumor growth and migration by targeting key substrate binding sites, showing superior efficacy over existing treatments. They also modulate SDH protein expression, suggesting a promising dual-targeting strategy for cancer therapy. This study sheds light on SDH function in cancer-related metabolic dysfunction and underscores the potential of SDH modulation as a therapeutic strategy for lung cancer and beyond.\u003c/p\u003e","manuscriptTitle":"Efficient identification of new small molecules targeting succinate dehydrogenase in non- small cell lung cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-08 06:51:17","doi":"10.21203/rs.3.rs-4197549/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2ead70ae-82e0-4b42-900b-632c3fb5594b","owner":[],"postedDate":"April 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-15T03:09:21+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-08 06:51:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4197549","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4197549","identity":"rs-4197549","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}