Nintedanib inhibits the VEGFR-ERK signaling pathway in human KRAS-mutated cancer cells

Nintedanib inhibits the VEGFR-ERK signaling pathway in human KRAS-mutated cancer cells | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Nintedanib inhibits the VEGFR-ERK signaling pathway in human KRAS-mutated cancer cells Sivasundaram Karnan, Akinobu Ota, Muhammad Nazmul Hasan, Toshinori Hyodo, and 16 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8370175/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 KRAS mutations are significant drivers in various cancers, and existing drug discovery efforts targeting these mutations have largely been unsuccessful, highlighting the need for more effective therapies. In this study, screening library, which contains 1374 chemical compounds, identified Nintedanib, a VEGFR inhibitor, as having a potent and selective antiproliferative effect against KRAS-mutant cells, surpassing other VEGFR inhibitors. Nintedanib effectively suppressed tumor growth in xenografted mice with KRAS mutations and was found to significantly inhibit phosphorylated VEGFR2 levels and its downstream signaling molecules pAKT and pERK in KRAS-mutant cells, suggesting that VEGFR2 inhibition impacts the oncogenic AKT/ERK pathway. Furthermore, in VEGFR2-knockout cells, KRAS-GTP activity was reduced by inhibiting the SOS1 protein, which led to decreased phosphorylation of ERK, AKT, and DRP1, inducing apoptosis. Notably, overexpression of KRASG12D augmented VEGFR2 expression, establishing a positive feedback loop between KRAS mutations and VEGFR2 signaling within the ERK pathway. Immunohistochemical analyses of pancreatic cancer tissues revealed high VEGFR2 expression in 83% (67/80) of samples, significantly exceeding levels observed in normal pancreatic tissues. These findings highlight VEGFR2 as a promising molecular target and propose a novel therapeutic avenue for KRAS-mutant cancers. Biological sciences/Cancer/Cancer therapy/Targeted therapies Biological sciences/Drug discovery/Drug screening/Phenotypic screening Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction KRAS mutations play a significant role in the development and progression of various cancers, particularly pancreatic, colorectal, and lung cancers [1,2,3]. The high mutation rate of KRAS in pancreatic cancer, estimated at 70-90%, correlates with a dismal five-year survival rate of less than 5%, emphasizing the urgent need for more effective therapeutic strategies [2,4,5]. While the EGFR kinase inhibitor erlotinib has received approval as a treatment option, its impact on survival has been limited [5,6,7,8,9]. In colorectal cancer, anti-EGFR monoclonal antibodies have been successfully deployed; however, the presence of RAS mutations severely compromises their efficacy, rendering them ineffective [6,7,10,11]. Similarly, in the context of lung cancer, erlotinib is commercially available for patients with EGFR mutations but has been shown to be ineffective in those with KRAS mutations [12]. In recent years, however, advancements in drug discovery and deeper understanding of KRAS biology have led to some breakthroughs. For instance, the development of small molecule inhibitors that specifically target KRAS G12C mutations has shown promise in preclinical studies and clinical trials. Drugs like sotorasib (AMG 510) and adagrasib (MRTX849) have received attention for their ability to selectively inhibit the G12C variant of KRAS, leading to meaningful clinical responses in patients with tumors harboring this specific mutation [10,11,13,14,15,16,17,]. However, a broader challenge remains because many variants lack defined binding pocket for effective inhibitor binding. As a result, research continues to refine our understanding of RAS biology and to develop innovative therapeutic strategies that effectively target these persistent oncogenic drivers [18,19]. Given the critical role of mutant KRAS in tumorigenesis, there is an urgent need to explore novel therapeutic avenues. Despite the centrality of mutant KRAS in cancer cell proliferation, the development of direct KRAS inhibitors has faced significant challenges due to the absence of unique structural characteristics that could serve as drug targets [13,20]. Moreover, existing inhibitors targeting downstream signaling or lipid modifications have yielded limited effectiveness [14,21]. From microarray analysis, we found that VEGF signaling molecules are increased in KRAS mutant cells. Therefore, a deeper understanding of the regulation of KRAS and its upstream signaling molecules, particularly the vascular endothelial growth factor receptor (VEGFR), is necessary. This knowledge could lead to the development of new therapies for cancers associated with KRAS mutations. KRAS mutations play an important role in cell signaling pathways that determine cell proliferation and survival [15,18]. As noted above, mutations typically occur in the GTP-binding pocket, particularly at residues 12, 13, and 61[20, 21, 22]. These mutations inhibit RAS GTPase activity, resulting in a state of sustained activity that continuously signals downstream pathways without the usual regulatory mechanisms provided by RAS GTPase activating protein (GAP) [23]. To further explore the molecular dynamics, it is insightful to refer to the role of the Son of sevenless (SOS) family of guanine nucleotide exchange factors (GEF) that activate RAS by promoting the exchange from the GDP-bound state to the GTP-bound state. [20,24]. Associated with RAS mutations, hyperactive signaling is further exacerbated by enhanced SOS activity and contributes to the oncogenicity of mutant RAS proteins [25]. Studies of SOS1 interaction with its mutant RAS proteins have provided valuable insights into potential therapeutic strategies [26]. In our VEGFR2-KO/PL8 KRAS -mutant cells, inhibition of SOS1 reduced KRAS-GTP activity, leading to decreased phosphorylation of ERK, AKT, and DRP1, and ultimately induced apoptosis. In our study, we introduced mutation at the G12 position of the KRAS gene in various human somatic cells and myeloma cell lines. This approach aimed to elucidate the altered molecular functions resulting from KRAS mutations and to identify novel therapeutic targets. Additionally, we screened a library of pharmacological agents and identified nintedanib, an intracellular tyrosine kinase inhibitor, as a potent inhibitor of cell survival in KRAS mutant contexts. Our findings suggest that nintedanib selectively inhibits the proliferation of KRAS mutant cells, warranting further investigation as a potential candidate for targeted therapy in KRAS-driven malignancies. Results Establishment of KRAS mutant human pancreatic cells To assess the role of KRAS mutations in pancreatic epithelial cells, we generated KRAS -mutant HPNE cell clones using the CRISPR-Cas9 prime editing system (PE max + epegRNAtevopreQ 1 ) targeting exon 2 of the KRAS gene in the hTERT-immortalized HPNE cell lines (Fig. 1A). Two KRAS G12D knock-in clones and one KRAS WT control clone were successfully isolated (designated HPNE- KRAS G12D #1 , HPNE- KRAS G12D #2 , and HPNE- KRAS WT ). Sanger sequencing confirmed hetero-allelic G12D knock-in events in the mutant clones (Fig. 1B). KRAS G12D knock-in enhances cell proliferation and clonogenicity in HPNE Cells Cell growth analysis using the MTT assay revealed significantly enhanced proliferation in KRAS G12D clones compared to the parental HPNE and KRAS WT control cells (Fig. 1C). Furthermore, KRAS G12D clones formed a greater number of colonies in soft agar assays relative to control cells (Fig. 1D). Transwell migration assays also indicated a marked increase in migratory capacity in KRAS G12D cells (Fig. 1E). These findings underscore the oncogenic potential of KRAS G12D in driving proliferation, anchorage-independent growth, and migration in HPNE cells . KRAS mutation induces the expression of KRAS-related molecules. cDNA microarray analysis comparing KRAS G12D clones with control cells identified 95 genes upregulated (>5-fold) and 13 genes downregulated (<0.2-fold) in KRAS G12D cells (Fig. S1A, Tables S1–S2). Pathway enrichment using Panther Classification Analysis highlighted the activation of cell proliferation pathways such as EGF, FGF, and VEGF signaling (Fig. S1B). Gene Set Enrichment Analysis (GSEA) further confirmed the activation of VEGF_A_UP.V1 and KRAS_DF.V1 oncogenic gene sets in KRAS G12D clones (Figs. S2A–S2B). Western blotting validated the elevated expression of VEGF-A in KRAS G12D cells relative to KRAS WT cells, implicating KRAS G12D in modulation of the VEGF-VEGFR axis (Fig. S1C). Screening of 1,374 pharmacological compounds for selective efficacy in KRAS-mutant cells We next performed a drug screening assay using the Selleck L2000 library (catalog number Z295656-384), which contains 1,374 chemical compounds, including known FDA-approved drugs. The screen was conducted using KRAS-mutant cells ( KRAS G12A Sachi and KRAS G12D HPNE cell clones) and corresponding KRAS wild-type controls (Sachi and HPNE cells). A summary of the results is provided in Supplementary Table S3. Out of the 1,374 compounds tested, 677 (49%) showed antiproliferative activity in both KRAS G12A Sachi and KRAS G12D HPNE cells compared with KRAS WT counterparts. To identify compounds with selective efficacy in KRAS-mutant cells, we applied a threshold of at least 25% greater viability reduction in mutant versus wild-type cells. Based on this criterion, 34 compounds were identified in KRAS G12A Sachi cells and 205 in KRAS G12D HPNE cells, with six compounds (Nintedanib, Celecoxib, Cediranib, Imatinib Mesylate, Enasidenib, and Gefitinib) common to both cell lines (Fig. 2A). Notably, among the top 10 candidate compounds, three of them (Nintedanib, Cediranib, and Axitinib) -targeting the VEGF signaling pathway (Fig. 2B), highlighting the potential importance of VEGFR inhibition in KRAS -mutant contexts. We subsequently examined all VEGF- targeting inhibitors in the library identifying 21 compounds, of which at least 16 showed minimal antiproliferative activity in both of the cell lines (Fig.S3). A detailed summary of their effects on cell viability is provided in Supplementary Table S4. Nintedanib exerts best antiproliferative effects on KRAS mutant cancer cells. Next, we compared the efficacy of two VEGFR inhibitors identified from our screening nintedanib and axitinib, and included an additional VEGFR inhibitor, motesanib, for evaluation in KRAS -mutant cell lines. MTT assays and IC₅₀ analyses revealed that nintedanib exhibited the strongest antiproliferative effect against KRAS-mutant cells among the VEGFR inhibitors tested. Notably, nintedanib significantly reduced the cell viability not only in cells with induced KRAS G12D and KRAS G12A mutations (Sachi, HPNE and HBEC3-KT) (Fig. 2C) but also in several cancer cell lines harboring spontaneous KRAS mutations A549, Lu-99A, DLD-1, Sw-480, PL8, AsPc-1, HCT116, PL5 (Fig. 2D; Table S5).The mean IC 50 value of Nintedanib was approximately 20 μM for KRAS wild-type cells and 5.0 μM for KRAS mutant cells (Fig. S4 and Table S5). These results strongly suggest that nintedanib preferentially suppresses the proliferation of KRAS mutant cancer cells. Nintedanib promotes mitochondrial fusion processes and triggers apoptosis in KRAS mutant cell lines To elucidate the biochemical and molecular mechanisms underlying the action of nintedanib on KRAS mutant cancer cells, we assessed mitochondrial morphology following nintedanib treatment using MitoTracker, a dye that labels functional mitochondria independent of cell viability. Confocal microscopy revealed that nintedanib clearly increased the mitochondrial fusion signals, which were characterized by an elongated tubular network structure, in KRAS mutant HCT116, PL8, Lu-99A cells (Fig. 3A). We then assessed the effect of nintedanib on the phosphorylation of dynamin-related protein 1 (DRP1), a central mediator of mitochondrial fission. Remarkably, treatment with nintedanib attenuated the phosphorylation of DRP1 in KRAS mutant cells, suggesting a regulatory effect of nintedanib on mitochondrial fission processes (Fig. 3A and 3B). Western blot analyses further confirmed that nintedanib treatment resulted in reduced phosphorylation levels of several key signaling proteins, including VEGFR1, VEGFR2, ERK, and AKT, (Fig. 3B). Furthermore, the addition of nintedanib to KRAS mutant cell lines (HCT116, PL8, Lu-99A, and HPNE- KRAS G12D ) led to a significant increase in the percentage of apoptotic cells, indicating that nintedanib effectively induces apoptosis in these KRAS mutant strains (Fig. 3C). Similarly, the cleaved Caspase3 level was markedly increased in the nintedanib-treated KRAS mutant cells (Fig. 3B). To further explore the mechanism underlying nintedanib-induced apoptosis, we measured intracellular reactive oxygen species (ROS) levels using the DCFH-DA assay. Notably, nintedanib treatment markedly increased ROS production in KRAS mutant cells (HPNE- KRAS G12D , HCT116, PL8, Lu-99A), whereas ROS levels in KRAS wild-type cells (HBEC3-KT and HPNE-WT) remained unchanged under both treated and non-treated conditions (Fig. 3D). In summary, our findings suggest that nintedanib selectively induce apoptosis through mitochondrial hyperfusion and increased oxidative stress in KRAS mutant cells. VEGFR2 regulates the activity of KRAS-GTP in the cancer cell line. To elucidate the role of VEGFR2 on KRAS -mutated cancer cells, we created VEGFR2 knockout (referred to as VEGFR2-KO/PL8) cell clones #1 and #2 using a KRAS-mutated pancreatic cancer cell line PL8 by targeting exon 20 of the KDR / VEGFR2 gene (Fig. 4A). Sanger sequence and western blot analyses confirmed the successful knockout of VEGFR2 (Figs. 4B and 4C). Western blot analysis revealed that SOS1, RAS-GTP, and the phosphorylation levels of Akt, ERK, and DRP1 readily decrease in VEGFR2 -KO/PL8 cells, compared to those in parental cells. In addition, the protein expression of pro-apoptotic proteins Bax and cleaved caspase-3 increased, while that of anti-apoptotic Bcl2 decreased in the VEGFR2 -KO/PL8 cell clones (Fig. 4C). Furthermore, protein expression of DRP1 clearly decreased in the VEGFR2 -KO/PL8 cells (Figs 4C and 4D). Interestingly, confocal imaging showed a substantial increase in the elongated, tubular mitochondrial structures in the VEGFR2 -KO/KRAS mutant cells, compared to the parental cells (Fig. 4D). To elucidate the involvement of KRAS-GTP on VEGFR2 expression, we introduced exogenous expression of KRAS G12D in 293T cells and a mouse fibroblast cell line 3T3 cells. Exogenous KRAS G12D clearly increased the expression levels of VEGFR2, suggesting that mutant KRAS G12D is inducing phosphorylation of VEGFR2 mediated oncogenic signal (Fig 4E). VEGFR2 is preferentially expressed in human pancreatic cancer tissues To investigate the expression of VEGFR2 in human pancreatic cancer tissues, we performed immunohistochemical analysis with 80 human pancreatic cancers and 20 normal pancreatic tissues (Table S6 and Fig. 5A). Microscopic analysis detected 1 strong (3+), 35 moderate (2+), and 31 weak (1+) VEGFR2-positive signals in 80 pancreatic cancer tissues, whereas only one moderate and 3 weak signals in 20 normal pancreatic tissues (Table S6 and Figs. 5B- 5C). Accordingly, the positivity rate for VEGFR2 signals in pancreatic cancer tissues (67 of 80 samples; 83%) was significantly higher than that in the normal pancreatic tissues (4 of 20 samples; 20%; Fig. 5D), suggesting that VEGFR-mediated signaling is active in pancreatic cancer tissues. Nintedanib significantly retards tumor growth in PL8 xenograft mice. Finally, we evaluated the effect of nintedanib on tumor growth in vivo using KRAS -mutated pancreatic cancer cell line PL8 with immunodeficient nude mice. Of note, administration of nintedanib led to a significant decrease in tumor growth compared to the vehicle control group, as demonstrated in Figs. 6A and 6B. Importantly, treatment with nintedanib did not lead to significant weight losses in mice (Fig. 6C). Moreover, blood chemistry tests revealed that administration of nintedanib did not affect levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) (Fig. 6D). These findings support the hypothesis that targeting VEGFR with nintedanib is a viable therapeutic strategy for KRAS -mutated pancreatic cancers, highlighting its potential as a promising candidate for molecular-targeted anticancer therapies. Discussion KRAS mutations are frequently observed in several aggressive malignancies, including pancreatic, colorectal, lung, and certain hematological cancers. These mutations leads to constitutive activation of downstream signaling pathways, notably MAPK and PI3K/AKT pathways [27]. Current anti-cancer therapies targeting KRAS remain limited, largely due to the absence of binding pockets on the KRAS protein, as well as unknown molecular mechanism regulating KRAS-mediated signaling pathway in KRAS mutated tumors. Therefore, the development of novel therapeutic strategies remains a major unmet clinical need [28, 29]. Our findings highlight the potential of nintedanib as a promising candidate for targeting KRAS -mutated cancers. In our screening with a large chemical library, nintedanib emerged as a potent agent that selectively inhibits the proliferation of KRAS -mutant cells. This selectivity is particularly noteworthy, considering that many existing efforts to directly target KRAS have been unsuccessful, largely due to the protein’s "undruggable" nature [13]. In this study, we identified one of the upstream signaling components towards KRAS, specifically VEGFR2, as a candidate molecule in our human cell model. Indeed, VEGFR2 plays a pivotal role in maintaining KRAS-mediated oncogenic signaling [25]. MTT assays demonstrated that nintedanib exhibits significantly lower IC 50 values in KRAS -mutant cells compared to their wild-type counterparts, underscoring its selectivity. Importantly, nintedanib demonstrated superior antiproliferative efficacy compared with other VEGFR inhibitors, such as axitinib and motesanib, across various cellular and mutational contexts. Mechanistically, nintedanib suppressed downstream signaling molecules, including pAKT and pERK, indicating thatVEGFR2 inhibition disrupts critical survival and proliferation pathways. Its enhanced efficacy is likely due to broader activity against multiple tyrosine kinases, including FGFRs and PDGFRs, in addition to VEGFR2, which amplifies anti-angiogenic and anti-proliferative effects. Combined with favorable pharmacokinetic properties and dosing advantages, these features likely account for nintedanib’s superior clinical and preclinical performance. Additionally, the induction of apoptosis in KRAS -mutant cells was accompanied by mitochondrial hyperfusion and elevated ROS, suggesting that nintedanib disrupts mitochondrial homeostasis and redox balance to selectively compromise the survival advantage conferred by mutant KRAS . An intriguing aspect of our study is the regulatory feedback loop identified between KRAS-GTP and VEGFR2 expression. Overexpression of KRAS G12D resulted in elevated VEGFR2 protein levels, suggesting a complex interplay that may contribute to tumor aggressiveness in KRAS-driven cancers [30]. Furthermore, our knock-in cell lines and KRAS mutant cells demonstrated increased VEGFR2 phosphorylation. Recent reports further support the findings that KRAS mutations are associated with enhanced VEGFR2 phosphorylation in both tumor vasculature [31] and cancer cells. KRAS mutations can drive metabolic reprogramming that modulates VEGFR2 activity [32]. Additionally, KRAS -driven cancers show resistance to anti-VEGF therapies, which correlate with alterations in VEGFR2 signaling pathways [33]. Collectively, these data suggest that KRAS mutations promote VEGFR2 activation, thereby contributing to tumor angiogenesis and therapy resistance while nintedanib selectively counteracts this process by inducing apoptosis and suppressing tumor growth. Supporting this further, VEGFR2 knockout models using PL8 cells, demonstrated that loss of VEGFR2 decreased in both SOS1 protein level and KRAS-GTP activity, accompanied by reduced AKT-ERK signaling and enhanced apoptosis. The result strongly suggests that VEGFR2 plays a pivotal role in maintaining KRAS activity in KRAS -mutant cell. Recent evidence indicates that ERK2-dependent phosphorylation of Drp1 plays a critical role in KRAS -driven tumor growth by facilitating mitochondrial fission, which is essential for metabolic reprogramming and tumor progression, particularly in pancreatic cancer [34,35,36,37]. Inhibition of Drp1 can disrupt glycolytic flux and impair mitochondrial metabolic functions in cells harboring oncogenic KRAS [38,39,40]. In this study, treatment with nintedanib in KRAS -mutant cells reduces Drp1 activity and mitochondrial fission in VEGFR2-KO KRAS -mutant cells. Consistent with these findings, VEGFR2 inhibition by nintedanib suppressed the KRAS mutation driven increase in mitochondrial fission, suggesting that nintedanib can also block KRAS downstream proliferation signals mediated through mitochondria, highlighting its potential as a highly effective molecular targeted therapy Our immunohistochemical data reveal that VEGFR2 is predominantly expressed in KRAS -mutant cell lines and patient-derived pancreatic cancer tissues. IHC analysis of human pancreatic cancer samples revealed significantly higher VEGFR2 expression in tumor tissues compared with normal tissue, with an 83% positivity rate suggesting VEGFR2’s involvement in KRAS -driven oncogenesis and its potential as a biomarker for disease progression and therapeutic targeting. In vivo , nintedanib significantly inhibited tumor growth in KRAS mutant xenograft models without notable toxicity, as evidenced by stable body weights and normal liver enzyme levels. These results are promising, as tolerability remains a critical consideration in cancer therapy [8]. Nevertheless, our study has limitations. The reliance on tumor cell lines, cell line-derived xenografts (CDX), and tissue samples restricts the translatability of our findings. Future studies should incorporate patient-derived xenograft (PDX) models, which better recapitulate the tumor microenvironment and heterogeneity, as shown in prior research assessing nintedanib’s efficacy in breast, lung, and pancreatic and kidney cancers [41,42,43,44]. Larger, comprehensive studies are necessary to validate these preliminary findings and establish clinical relevance. In conclusion, our study identifies nintedanib as a potent therapeutic candidate against KRAS -mutant cancers by targeting the VEGFR2-ERK signaling axis. The correlation between KRAS mutations and VEGFR2 expression, supported by molecular and clinical data, suggests VEGFR2 as both a driver and a biomarker of KRAS-driven oncogenesis. Further clinical studies are warranted to assess the utility of nintedanib in treating patients harboring KRAS mutations. Materials and Methods Cell culture Human normal epithelial cell lines hTERT-HPNE (CRL-4023) and HBEC3-KT (CRL-4051) were obtained from the American Type Culture Collection (ATCC; Manassas, VA). Additional cell lines, including A549, Lu-99A, DLD1, HCT116, Sw-480, AsPC-1, PL5, and PL8, were generously provided by Dr. Ben Ho Park at Johns Hopkins University (Baltimore, MD). HBEC3-KT cells were cultured in Ham’s F-12 medium supplemented with 10% fetal bovine serum (FBS) and 1% penicillin. In contrast, the remaining cell lines (HPNE, Sachi, A549, Lu-99A, DLD1, HCT116, Sw-480, AsPC-1, PL5, and PL8) were maintained in RPMI-1640 medium (Wako, Osaka, Japan), also supplemented with 10% FBS (Sigma) and 1% penicillin-streptomycin (Wako). All cultures were incubated at 37°C in a humidified atmosphere containing 5% CO 2 . Cells were routinely subcultured upon reaching approximately 80% confluence, maintaining optimal growth conditions. The culture media were changed every 2-3 days, and cell viability and morphology were assessed regularly to ensure healthy growth and proper characteristics of the cell lines. Gene Knock-in Using the Prime editing System The epegRNA plasmid was constructed utilizing a Golden Gate cloning strategy, involving the assembly of a BsaI-digested epegRNA backbone (pU6-tevopreq1-GG-acceptor, Addgene: #174038) [45,46]. Following digestion, the reaction was incubated at 37°C for 4 hours. Verification of proper digestion was performed using gel electrophoresis, where the expected bands for a correctly digested pegRNA backbone appeared at 2.2 kb. The 2.2 kb fragment was isolated using the Qiagen Gel Extraction Kit. Three annealed double-stranded DNA fragments—comprising the epegRNA spacer sequence, epegRNA scaffold, and epegRNA extension sequence (which includes the PBS and RT template)—were prepared based on the primers listed in Supplementary Table S7. These fragments were mixed and ligated with the epegRNA backbone. To establish a knock-in clone, we transfected 1 µg of the epegRNA G12D plasmid along with the pCMV-PEmax-P2A-GFP (Addgene #180020) plasmid into HPNE and HBEC3-KT cells (1 × 10 6 cells) and using a 4D-Nucleofector instrument (Lonza Japan, Tokyo, Japan). After 3 days post-transfection, GFP-expressing cells were sorted via fluorescence-activated cell sorting (FACS) using a BD FACSAria™ III Cell Single-cell sorting was performed using a BD sorter (BD Biosciences, San Jose, CA, USA). An individual clone was isolated, expanded, and later used for downstream biological assays. Gene Knock-in Using the Crispr Editing System The gRNA plasmid was constructed via Golden Gate cloning using BsaI-digested PX458 (Addgene #48138). The backbone was digested at 37°C for 1 hour, purified by Qiagen Gel Extraction, and ligated with an annealed double-stranded gRNA based on primer 5’-AAACTTGTGGTAGTTGGAGC-’. Additionally, a 900 bp exon 2 fragments from RPMI-8226 genomic DNA was amplified and cloned into pcDNA3.1. For knock-in, 1 μg of PX458-RAS gRNA and pcDNA3.1 KRAS G12A donor were co-transfected into 1×10 6 Sachi cells via 4D-Nucleofector. After 3 days, GFP-positive cells were sorted by FACS, single clones isolated, expanded, and used for further analysis. Gene knockout using the CRISPR/Cas9 system We used CRISPR/Cas9 system to knockout VEGFR2 in PL8 cell line, following established procedures [47]. The pSpCas9(BB)-2A-GFP (PX458) plasmid was generously provided by Feng Zhang (plasmid #48138; Addgene, Watertown, MA, USA) [48]. Briefly, sgRNA sequences were chosen using an optimized CRISPR design tool (http://crispr.mit.edu/). The selected sgRNA sequences for VEGFR2 was 5′-GAAACCTGTCCACTTACCTG -3′ in exon 20. Plasmids expressing hCas9 and sgRNA were generated by ligating oligonucleotides into the BbsI site of PX458 ( VEGFR2 /PX458). To construct the expression vector KRAS G12D , cDNA fragments of KRAS G12D was amplified by PCR using Prime STAR Max DNA polymerase (Takara Bio, Otsu, Japan). The cDNA fragments were then introduced into the PiggyBac expression vector (Addgene Cat no #203312). Backbone PiggyBac was used as a control vector. To establish a knockout (KO) clone, 1 μg of VEGFR2 /PX458 plasmid was transfected into the PL8 cell cells (1 × 10 6 cells) using a 4D-Nucleofector instrument (Lonza Japan, Tokyo, Japan). After 3 days, GFP-expressing cells were sorted using fluorescence-activated cell sorting (BD FACSAria™ III Cell Sorter; BD Biosciences, San Jose, CA, USA). A single clone was selected, expanded, and utilized for the biological assays. Cell Growth Assay Cell proliferation was evaluated using the MTT colorimetric assay. Cells were seeded into 96-well plates at a density of 1 × 10³ cells per well and allowed to adhere and grow for predetermined time intervals (0, 24, 48, and 72 hours). At each time point, 10 μl of MTT solution (5 mg/ml; Sigma-Aldrich) was added to each well, followed by incubation at 37°C for 4 hours to enable viable cells to convert MTT into purple formazan crystals. After incubation, the formazan was completely solubilized, and absorbance was measured at 595 nm using a SpectraMAX M5 microplate reader (Molecular Devices, Sunnyvale, CA, USA). The measured optical density (OD) correlated directly with the number of metabolically active cells. All experiments were performed in triplicate, and data are presented as mean ± standard deviation (SD). Western Blot Analysis Western blot analysis was performed to detect specific proteins in sample extracts as previously established [48,49]. Proteins were first separated by SDS-PAGE, then transferred to a PVDF membrane (Millipore Cat. no IPVH00010), which was blocked with 5% non-fat milk in TBST to minimize non-specific binding. Incubation with primary antibodies (listed in Table S8) occurred overnight at 4°C, followed by washing and application of HRP-conjugated secondary antibodies for 1 hour at room temperature. Immune complexes were detected using ImmunoStar LD chemiluminescent substrate (FUJIFILM Wako Chemicals USA Cat no 292-69903), and bands were visualized with a LAS-4000 image analyzer. Quantification of protein expression levels was conducted using densitometry via ImageJ software, with normalization to GAPDH as a loading control. All experiments were performed in triplicate for reproducibility. Soft agar colony formation assay The soft agar colony formation assay was carried out as described previous [50, 51]. The number of colonies was counted using Colony Counter software (Keyence, Tokyo, Japan). The data are presented as mean ± SEM (n = 5). Migration assay Ten thousand cells suspended in 100 μL serum-free medium were added into the upper chambers of a Transwell (8 μm for 24-well plate; Millipore, Tokyo, Japan), as described previously [49] and culture medium was added into the lower chambers. After 24 hours, the cells were fixed by formalin and stained by 0.1% crystal violet. The number of colonies was manually counted under a microscope. Annexin V assay Cells were plated into six-well culture plates (5 × 10 5 cells/well) and treated with nintedanib (7.5 µg/mL) for 48 hours. Subsequently, the cells were exposed to annexin V (Ax)-FITC and propidium iodide (PI) (10 μg/mL) at 25°C for 15 minutes. The fluorescence intensities were quantified using fluorescence-activated cell sorting (FACS) analysis (LSRFortessa X-20 Flow Cytometer, BD Biosciences, Franklin Lakes, NJ, USA). [52] Immunofluorescence The cells were cultured on glass coverslips and fixed with a 4% paraformaldehyde solution for 20 minutes at 25°C. Subsequently, the cells were permeabilized with phosphate-buffered saline (PBS) containing 0.1% Triton X-100, blocked in PBS containing 7% serum for 30 minutes, and then incubated with primary antibody (pDRP1) followed by Alexa Fluor-conjugated secondary antibodies (Invitrogen). Cell staining was conducted using MitoTracker (stock solution 1 mM; diluted at 1:10,000) for 1 hour at 37°C to visualize the mitochondria. Following staining, the cells were washed with PBS and fixed with cold paraformaldehyde (3.2% in PBS) for 20 minutes at room temperature. After additional washing steps, the samples were mounted using PermaFluor, and images were captured using the FLUOVIEW FV3000 Series of Confocal Laser Scanning Microscopes. DCFH–DA-based DCF Assay Cells were seeded into six-well plates at a density of 3 × 10 5 cells per well. After 24 hours, cells were exposed to 5.0 μM nintedanib for one day. Subsequently, cells were incubated with 10 μM DCFH–DA (2’,7’-dichlorodihydrofluorescein diacetate) in culture medium for 45 minutes, protected from light. After incubation, the dye was removed, and cells were washed with PBS. Cells were then trypsinized, collected by centrifugation at 1,000 rpm for 5 minutes, and resuspended in PBS in 0.5-mL tubes on ice. Intracellular ROS levels were assessed by flow cytometry using LSRFortessa X-20 (BD Biosciences). [53] Immunohistochemistry Immunohistochemical analysis was conducted following previously established protocols [53, 54]. A human Pancreas cancer tissue array (PA1002b; US Biomax, Rockville, MD, USA) was utilized. The tissue sections were treated with primary antibodies against VEGFR2 (2 μg/mL). Negative controls included normal rabbit IgG or omission of the primary antibody. Immunoreactivity was evaluated independently by two investigators (S.K. and H.M.), and staining intensity was scored as strong (3+), moderate (2+), or weak (1+). or negative (0). cDNA Microarray Analysis The cDNA microarray analysis was conducted in accordance with the manufacturer's protocol (Agilent Technologies), as previously described [48]. Briefly, cDNA synthesis and cRNA labeling were performed using cyanine 3 (Cy3) dye with the Agilent Low Input Quick Amp Labeling Kit (Agilent Technologies). The Cy3-labeled cRNA was then purified, fragmented, and hybridized onto a Human Gene Expression 8x60K v2 Microarray Chip, which contains 62,969 Entrez Gene RNAs, utilizing the Agilent Gene Expression Hybridization Kit. Raw and normalized microarray data have been deposited in the Gene Expression Omnibus (GEO) database at the National Center for Biotechnology Information (accession number GSE312012; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE312012). Gene set enrichment analysis was performed according to standard protocols. Screening of anticancer drugs library A library consisting of 1,374 compounds (Selleck Catalog No. L2000-Z295656, FDA-Approved Drug Library 1300) was screened. Specifically, 500 cells of each of the following lines were seeded into 384-well cell culture plates: Sachi-KRAS WT , HPNE-KRAS WT , Sachi-KRAS G12A , and HPNE-KRAS G12D (KRAS gene mutants). The cells were then incubated at 37 °C for 24 hours. Following this, a library of 1,543 compounds was added to each well to achieve a final concentration of 7.5 M, and the cells were incubated at 37 °C for an additional 72 hours. After incubation, cell viability was assessed using the MTT assay. The absorbance was measured at 595 nm using a SpectraMAX M5 spectrophotometer (Molecular Devices, Sunnyvale, CA, USA). Control wells containing no drug treatment were considered to have 100% viability, allowing for the calculation of relative cell viability following drug exposure. Xenograft experiments All animal experiments were conducted in accordance with the protocols (approval number-2022-20) approved by the ethical committee of Aichi Medical University and followed established guidelines. Female Nude mice (BALB/cSlc-nu/nu) (5-week-old, each weighing 14–15 g) were purchased from CLEA Japan, Inc (Tokyo, Japan) and bred at the Institute of Animal Experiments in Aichi Medical University in specified pathogen-free animal facilities. PL8 cells (1 × 10 7 cells) were injected subcutaneously into these mice. When the inoculated tumor reached ~60 mm 3 (day 0), the mice were randomly divided into two groups (treatment and control groups). Nintedanib (15 mg/kg body weight) was intraperitoneally administered on days 0, 3, 5, 7, 9, 11and 13 to each mouse in the treatment group. The control group received PBS as vehicle control. The tumor volume was measured on day 0, 3, 5, 7, 9, 11 and 13 and calculated using the modified ellipsoid formula (1/2 × length × width 2 ). Blood chemistry After two weeks of nintedanib treatment, both control and treatment group mice were anesthetized by isoflurane and about 1 ml of blood were collected in heparin tube. After that blood samples were centrifuged at 800 × g for 20 min for serum collection. Serum was then examined for aspartate aminotransferase (AST) and alanine aminotransferase (ALT) by the Nagahama Life Science Laboratory (Oriental Yeast Co., Ltd., Shiga, Japan). Statistical analysis Data are expressed as mean ± standard error (SE). Differences among groups were evaluated using one-way analysis of variance (ANOVA) followed by Dunnett’s post hoc test. All statistical analyses were performed using GraphPad Prism and/or SPSS version 23.0 (SPSS Inc., Chicago, IL, USA). Declarations Competing interest This publication has no conflicts of interest, and there has been no substantial financial support for this work that could have influenced its outcome. The manuscript has been reviewed and endorsed by all named authors, and there are no other individuals who meet the criteria for authorship but are not listed. All authors have consented to the order in which they are listed in the manuscript. Availability of data and materials All accessible data are provided either in the main manuscript or in the supplementary materials. Complete and unaltered western blot data utilized in the study are available in the supplementary information. Furthermore, specific inquiries, data, and materials can be obtained upon reasonable request to the corresponding author. Ethical standards The research was conducted in accordance with the ethical standards set by the Japanese Ministry of Health, Labour, and Welfare. All animal experiments were performed in compliance with the guidelines and regulations of both the Japanese government and Aichi Medical University regarding the care and use of experimental vertebrate animals, with approval from the university’s Animal Care and Use Committee. All recombinant DNA experiments were carried out by certified researchers following appropriate training and were approved by the Recombinant DNA Experiment Safety Committee of Aichi Medical University. Author contributions Conception and design: SK, AO Development of methodology: SK, MNH, AO Acquisition of data/Resources: SK, MNH, NJ, MTAS, MR, HI, YK, YL Analysis and interpretation of data: SK, MNH, LQM, HM, MW, MLR, TH, SI, TM Writing, review, and/or revision of the manuscript: SK, AO, MNH Administrative, technical, or material support: YH, TH, HK, ST, IH, SI Funding acquisition: SK, AO Study supervision: SK Acknowledgements We thank Dr. Y. Sekido from the Division of Molecular Oncology, Aichi Cancer Center Research Institute, for kindly providing the lung cell line (Lu-99A).This study received partial support from grants provided by the Ministry of Education, Culture, Sports, and Technology of Japan (MEXT, 19K08668, 22K08294 to Y.H., 19K09292, 22K08985, 25K12115 to SK, and 21K08426 to AO), a research grant from the Hori Science and Arts Foundation, and a research grant from the Hirose International Scholarship Foundation (SK). MNH, MTSA and NJ were supported by the Japanese Government (MEXT) Scholarship for Research Student. We would like to thank Takehiko Inaba and Natsumi Kodama at the Institute of Comprehensive Medical Research, Division of Advanced Research Promotion, Aichi Medical University, for their valuable contributions to this investigation. References Uniyal P, Kashyap VK, Behl T, Parashar D, Rawat R. KRAS Mutations in Cancer: Understanding Signaling Pathways to Immune Regulation and the Potential of Immunotherapy. Cancers (Basel). 2025; 17 (5). Norton C, Shaw MS, Rubnitz Z, Smith J, Soares HP, Nevala-Plagemann CD, et al. KRAS Mutation Status and Treatment Outcomes in Patients with Metastatic Pancreatic Adenocarcinoma. JAMA Netw Open. 2025; 8 (1): e2453588. Wolfgang CL, Herman JM, Laheru DA, Klein AP, Erdek MA, Fishman EK, et al. Recent progress in pancreatic cancer. CA Cancer J Clin. 2013;63(5):318-48. Bardeesy N, DePinho RA. Pancreatic cancer biology and genetics. 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Genome engineering using the CRISPR-Cas9 system. Nat Protoc. 2013; 8 (11):2281-308. Karnan S, Ota A, Murakami H, Rahman ML, Wahiduzzaman M, Hasan MN, et al. CAMK2D: a novel molecular target for BAP1-deficient malignant mesothelioma. Cell Death Discov. 2023; 9 (1):257. Wahiduzzaman M, Karnan S, Ota A, Hanamura I, Murakami H, Inoko A, et al. Establishment and characterization of CRISPR/Cas9-mediated NF2(-/-) human mesothelial cell line: Molecular insight into fibroblast growth factor receptor 2 in malignant pleural mesothelioma. Cancer Sci. 2019; 110 (1):180-93. Karnan S, Ota A, Murakami H, Rahman ML, Hasan MN, Wahiduzzaman M, et al. Identification of CD24 as a potential diagnostic and therapeutic target for malignant pleural mesothelioma. Cell Death Discov. 2020; 6 (1):127. Karnan S, Hanamura I, Ota A, Takasugi S, Nakamura A, Takahashi M, et al. CD52 is a novel target for the treatment of FLT3-ITD-mutated myeloid leukemia. Cell Death Discov. 2021; 7 (1):121. Karnan S, Hanamura I, Ota A, Vu LQ, Uchino K, Horio T, et al. ARK5 enhances cell survival associated with mitochondrial morphological dynamics from fusion to fission in human multiple myeloma cells. Cell Death Discov. 2024; 10 (1):56. Karnan S, Ota A, Hasan MN, Murakami H, Rahman ML, Wahiduzzaman M, et al. Targeting fatty acid synthase suppresses tumor development in NF2/CDKN2A-deficient malignant pleural mesothelioma. bioRxiv. 2024:2024.07.14.603191. Jahan N, Islam S, Sivasundaram K, Ota A, Naito M, Kuroda J, et al. Role of versican in extracellular matrix formation: analysis in 3D culture. Am J Physiol Cell Physiol. 2025; 328 (1):C245-C57. Additional Declarations There is NO Competing Interest. Supplementary Files TableS120251202.docx Table S1. Upregulated genes in KRASG12D cells TableS220251202.docx Table S2. Downregulated genes in KRASG12D cells TableS320251202.docx Table S3. Effect of 1374 inhibitors on the proliferation of KRAS mutants and KRASWT cells TableS420251202.docx Table S4. Effect of 22 VEGFR inhibitors on the proliferation of KRASG12D and KRASWT cells TableS520250202.docx Table S5. IC50 values of cell lines used in this study TableS620251202.docx Table S6. Summary of immunohistochemistry in this study TableS720251202.docx Table S7. Primer sets used in this study TableS820251202.docx Table S8. Antibodies used in this study KRASSupplementalFigure20251212.pdf Supplementary Figure 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8370175","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":561887263,"identity":"592f6bf1-99ec-42c7-ad92-a31e953bffd2","order_by":0,"name":"Sivasundaram 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(A)\u003c/strong\u003e Schematic representation of the prime editing mechanism using pegRNA and Cas9 nickase for precise genome editing. The pegRNA comprises a spacer (red) for target recognition, a scaffold (blue) for stability, a reverse transcription template (RTT, light green) for intended edit, a primer binding site (PBS, yellow) for reverse transcription initiation, and a 3′ tevopreQ\u003csub\u003e1\u003c/sub\u003estructural motif (purple) for increased pegRNA stability. Upon binding to the target genomic DNA (black and grey), the Cas9 nickase (green) induces a single-strand break in the opposite strand, creating a nick. The pegRNA subsequently hybridizes to the nicked DNA, enabling reverse transcriptase (pink) to extend and incorporate the desired sequence from the RTT. The edited strand is shown in black, with the complementary strand in light grey, demonstrating the of prime editing. \u003cstrong\u003e(B)\u003c/strong\u003e Genomic sequence validation of \u003cem\u003eKRAS \u003c/em\u003ein HPNE knock-in cell clones compared with parental cell. \u003cstrong\u003e(C)\u003c/strong\u003e MTT-based proliferation assay of parental HPNE cells, control HPNE- \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eWT\u003c/sup\u003e cell clone, and two HPNE-\u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003ecell clones (#1 and #2). The relative optical density (OD) at 595 nm was calculated by dividing the OD of day 0 at each time point (days 0, 1, 3, 5, and 7) and is presented as the mean ± SEM (n = 3). \u003cstrong\u003e(D)\u003c/strong\u003e Soft agar colony formation assay. Five hundred cells of each clone were seeded in a 12- well plate and cultured for 14 days, followed by MTT staining and imaging. Representative images (left) quantified colony numbers (right bar graph) are shown. Data represented mean ± SEM (n = 5). \u003cstrong\u003e(E)\u003c/strong\u003e Boyden chamber migration assay. Cells (2.5 × 10\u003csup\u003e5\u003c/sup\u003e cells/well) were seeded in transwell inserts placed in 24-well plates and allowed to migrate for 24 hours. The migrated cells were stained with crystal violet and imaged. The bar graph (right) shows quantification of migrated cells. Data represent mean ± SEM (n = 5).\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/f98850a280a80d8a3bf61dbb.jpg"},{"id":98489537,"identity":"a8ea3d69-db74-460f-91ad-7ce308d2aa5f","added_by":"auto","created_at":"2025-12-18 07:32:48","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":135589,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of VEGFR inhibitors targeting KRAS-mutant cells and their effects on cell viability.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(\u003cstrong\u003eA\u003c/strong\u003e) A total of 1,374 compounds were screened to assess their effects on cell proliferation using \u003cem\u003eKRAS\u003c/em\u003e mutant knock-in cell lines. The criterion for selecting active compounds was a reduction in cell viability by ≥25% more in mutant cells compared to wild-type cells (i.e., Sachi vs. Sachi-KRAS\u003csup\u003eG12A \u003c/sup\u003eand HPNE vs. HPNE-KRAS\u003csup\u003eG12D\u003c/sup\u003e). From this screen, 34 active compounds were identified in Sachi-KRAS\u003csup\u003eG12A\u003c/sup\u003e cells (grey) and 205 active compounds in HPNE-KRAS\u003csup\u003eG12D\u003c/sup\u003e cells (green), with six compounds commonly active in both \u003cem\u003eKRAS\u003c/em\u003e mutant cell lines. (\u003cstrong\u003eB\u003c/strong\u003e) Top 10 candidate compounds identified from the screening. Pattern-filled bar representing VEGFR inhibitors among the top hits. (\u003cstrong\u003eC\u003c/strong\u003e) Effect of axitinib, motesanib, and nintedanib on cell survival in various KRAS knock-in cell lines compared with KRAS wild type cells (HPNE, HBEC3-KT and Sachi) and (\u003cstrong\u003eD\u003c/strong\u003e) other cancer cell lines (A549, Lu-99A, DLD1, SW-480, HCT116, PL5, PL8, and AsPC-1). Cells were treated with indicated drug concentrations (20, 15, 10, 7.5, 5, 2.5, 1.25, 0.625, and 0 μM) for 72 hours. Cell viability was assessed using MTT assays (OD595) and survival percentages were calculated accordingly. Nintedanib, axitinib, and motesanib are represented by red, green, and purple lines, respectively. Data are shown as mean ± SEM (n = 3).\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/ef0d695641c3eaebf311aa46.jpg"},{"id":98623415,"identity":"fb41728e-8aa5-4aea-8167-f2671666df24","added_by":"auto","created_at":"2025-12-19 17:06:14","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":187237,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRole of Nintedanib in mitochondrial morphology and apoptosis in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eKRAS\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e-mutant cells (A)\u003c/strong\u003e Mitochondria were visualized using the MitoTracker (red) and nuclei were counterstained with Hoechst (blue), in HCT116 (upper left panel), PL8 (upper center panel), and Lu-99A (upper right) cells. Cells were immunostained with Drp1 antibody (green) and Hoechst (blue) in the mitochondria, as depicted in the left middle panel (HCT116), middle center panel (PL8), and middle right panels (Lu99A). \u003cstrong\u003e(B)\u003c/strong\u003e Western blot analysis of p-VEGFR1-Y1213, VEGFR1, p-VEGFR2-Y1175, VEGFR2, p-ERK-Thr202/Tyr204, tERK, p-AKT-S473, AKT, pDRP1-S616, DRP1, C-caspase3 and GAPDH in HCT116, PL8, Lu-99A and HPNE (\u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eWT\u003c/sup\u003e and \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e) cells treated with nintedanib (7.5 µM) for 48 h. \u003cstrong\u003e(C)\u003c/strong\u003e Flow cytometry analysis using Annexin V\u003csup\u003e+\u003c/sup\u003e/PI\u003csup\u003e+\u003c/sup\u003e staining. Representative plots of AxV-PI-based staining are presented on the left. The graphs on the right display the percentage of AxV+/PI+ apoptotic cells following nintedanib treatment (7.5 µM) for 48 h measured using LSRFortessa X-20 Flow Cytometer (BD Biosciences). Data are mean ± SE (n = 3). Asterisks denote significant differences between the nintedanib treatment cells and non-treatment cells (HCT116, PL8 cells, Lu-99A cells, HPNE, and HPNE-KRAS\u003csup\u003eG12D\u003c/sup\u003e) (*p \u0026lt; 0.05).\u003cstrong\u003e (D) \u003c/strong\u003eDCFH–DA-based DCF assay: Effect of DCFH-DH (10 M, 45 min) on reactive oxygen species production in Nintedanib-treated cells (Red) compared to non-treated cells (Blue) in HBEC3-KT (\u003cem\u003eKRAS\u003c/em\u003e-WT), HPNE (\u003cem\u003eKRAS\u003c/em\u003e-WT), HPNE (\u003cem\u003eKRAS-\u003c/em\u003emutant) and HCT116, PL8, Lu-99A (\u003cem\u003eKRAS\u003c/em\u003e-mutant) cell lines.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/fa99c216e719abaa47c2e4ba.jpg"},{"id":98623798,"identity":"3c79dd3e-3733-4a5e-a6cb-45aea7d15fd9","added_by":"auto","created_at":"2025-12-19 17:07:37","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":132066,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of KRAS GTP in PL8 VEGFR2-KO cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGeneration of neurofibromatosis type 2 (\u003cem\u003eVEGFR2\u003c/em\u003e) knockout (VEGFR2‐KO) cell clones using a CRISPR/Cas9 system with the human PL8 cell line. \u003cstrong\u003e(A) \u003c/strong\u003eA single\u003c/p\u003e\n\u003cp\u003eguide RNA sequence was designed against exon 20 of the \u003cem\u003eVEGFR2 \u003c/em\u003elocus. \u003cstrong\u003e(B)\u003c/strong\u003eThe genomic sequence analysis of VEGFR2 in PL8 cells was compared with that of parent cells. \u003cstrong\u003e(C)\u003c/strong\u003e Protein expression of SOS1, KRas-GTP, Total Kras, AKT-S473, AKT, ERK1/2 (Thr202/Tyr204), tERK, DRP1-S616, DRP1, Bcl2, C-caspase3, VEGFR2 and GAPDH analyzed by Western blotting in PL8, and PL8-VEGFR2-KO cells.\u003cstrong\u003e(D)\u003c/strong\u003e The mitochondria were visualized using the MitoTracker probe (red). Nuclei were stained with Hoechst (blue), pDRP1 (green) in PL8 (upper panel) and PL8-VEGFR2-KO (down panel). \u0026nbsp;\u003cstrong\u003e(E\u003c/strong\u003e) Effect of exogenous RAS GTP expression in 293T and 3T3 cells on the protein levels of pVEGFR2 in 293T and 3T3 cells\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/6ab2907fc8a603fd713712bc.jpg"},{"id":98624341,"identity":"f6a13b57-ef2a-4cfd-88e0-73e62390d107","added_by":"auto","created_at":"2025-12-19 17:08:20","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":191469,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImmunohistochemistry (IHC) for Vascular Endothelial Growth Factor Receptor (VEGFR2) expression\u003c/strong\u003e. \u003cstrong\u003e(A)\u003c/strong\u003e Expression in VEGFR2‐negative pancreas tissue pleural (case 81, 91 and 94) and VEGFR2‐positive pancreas tumor (case 47, 70 and 78). \u003cstrong\u003e(B)\u003c/strong\u003eSummary of IHC results in pancreas tumor tissues. The immunoreactivities were independently evaluated by 2 investigators. The intensity of staining was scored as strong (3+), moderate (2+), weak (1+), or negative (0). \u003cstrong\u003e(C) \u003c/strong\u003eViolin plot showing VEGFR2 scores (Y-axis) in normal and pancreatic tumor tissue. Scores were independently evaluated by two investigators. Statistical analysis was performed using the Mann–Whitney test; ****p \u0026lt; 0.0001. \u003cstrong\u003e(D)\u003c/strong\u003eThe bar graph represents the percentage of total number of cases with VEGFR2 expression (strong, moderate and weak) in the pancreas normal and tumor tissue.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/c9bf5b9ec48df51396e9ed02.jpg"},{"id":98489539,"identity":"c836b52c-50e2-461c-abc8-31b763d5d00a","added_by":"auto","created_at":"2025-12-18 07:32:48","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":94028,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEffect of Nintedanib on the growth of PL8 tumor cells in vivo\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePL8 cells (5 × 10\u003csup\u003e6\u003c/sup\u003e cells/mouse were subcutaneously xenografted into nude mice. Once tumors reached ~60 mm\u003csup\u003e3\u003c/sup\u003e (day 0), nintedanib (15 mg/kg body weight) or vehicle (PBS) was intraperitoneally administrated on days 0, 3,5,7, 9, 11 and 13 into xenografted mice \u003cstrong\u003e(A)\u003c/strong\u003e Representative image depicting tumor-bearing xenografted mice in each group. (B-C) Growth curves of \u003cstrong\u003e(B)\u003c/strong\u003e tumor volume (mm\u003csup\u003e3\u003c/sup\u003e) and \u003cstrong\u003e(C)\u003c/strong\u003e mouse body weight (g) during nintedanib treatment. Data are presented as mean ± SEM (n = 5). ****\u003cem\u003ep\u003c/em\u003e\u0026lt;0.0001, ns, not significant; two-way ANOVA. \u003cstrong\u003e(D)\u003c/strong\u003e Blood chemistry analysis (AST and ALT) following nintedanib treatment compared with vehicle control.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/d9fbde37c5fb64879c4b8217.jpg"},{"id":99790928,"identity":"fa74303b-fd10-48d7-b0f7-3046c56be639","added_by":"auto","created_at":"2026-01-08 12:58:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2290822,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/1c7edf32-dc4e-44a6-a8d6-89f45484c638.pdf"},{"id":98624279,"identity":"51dbf608-1be0-46e3-8eb5-589402fc30c9","added_by":"auto","created_at":"2025-12-19 17:08:15","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":23145,"visible":true,"origin":"","legend":"\u003cp\u003eTable S1. Upregulated genes in KRASG12D cells\u003c/p\u003e","description":"","filename":"TableS120251202.docx","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/61c6be2302b7398410b715b5.docx"},{"id":98624383,"identity":"e8d2b808-cbbd-4b30-af5b-caffd1d389ed","added_by":"auto","created_at":"2025-12-19 17:08:23","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":16917,"visible":true,"origin":"","legend":"\u003cp\u003eTable S2. Downregulated genes in KRASG12D cells\u003c/p\u003e","description":"","filename":"TableS220251202.docx","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/d721c463b2850a07e1e6ca17.docx"},{"id":98489540,"identity":"6dbf8c42-3610-41d9-b2ca-9bf2068295ec","added_by":"auto","created_at":"2025-12-18 07:32:48","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":307070,"visible":true,"origin":"","legend":"\u003cp\u003eTable S3. Effect of 1374 inhibitors on the proliferation of KRAS mutants and KRASWT cells\u003c/p\u003e","description":"","filename":"TableS320251202.docx","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/2054cfcbfb19195e23606e2b.docx"},{"id":98624667,"identity":"23499476-bdb6-445b-94e4-6137a091fa03","added_by":"auto","created_at":"2025-12-19 17:08:37","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":20872,"visible":true,"origin":"","legend":"\u003cp\u003eTable S4. Effect of 22 VEGFR inhibitors on the proliferation of KRASG12D and KRASWT cells\u003c/p\u003e","description":"","filename":"TableS420251202.docx","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/7f818f0d575a11f378c6f7c3.docx"},{"id":98623571,"identity":"90fd632a-0544-407a-af1f-7de07be37f6d","added_by":"auto","created_at":"2025-12-19 17:06:59","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":18775,"visible":true,"origin":"","legend":"\u003cp\u003eTable S5. IC50 values of cell lines used in this study\u003c/p\u003e","description":"","filename":"TableS520250202.docx","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/8229a43896849f1f46d8038e.docx"},{"id":98489541,"identity":"63ce6416-0a8f-43f9-9612-e75b564927cc","added_by":"auto","created_at":"2025-12-18 07:32:48","extension":"docx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":32378,"visible":true,"origin":"","legend":"\u003cp\u003eTable S6. Summary of immunohistochemistry in this study\u003c/p\u003e","description":"","filename":"TableS620251202.docx","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/8b375c76688c59b9a2af3c5a.docx"},{"id":98489547,"identity":"d39940ae-6df8-4cfc-9ab1-d0fab0d93cc4","added_by":"auto","created_at":"2025-12-18 07:32:48","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":16949,"visible":true,"origin":"","legend":"\u003cp\u003eTable S7. Primer sets used in this study\u003c/p\u003e","description":"","filename":"TableS720251202.docx","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/c83537aa46059b7e9b46089b.docx"},{"id":98624438,"identity":"41af59fc-2c3b-4141-8486-8277b3226949","added_by":"auto","created_at":"2025-12-19 17:08:25","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":18359,"visible":true,"origin":"","legend":"\u003cp\u003eTable S8. Antibodies used in this study\u003c/p\u003e","description":"","filename":"TableS820251202.docx","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/96e78f7e77c8ce8e5797d20a.docx"},{"id":98623441,"identity":"4626d8ba-3773-4855-a079-6a20a8fe8129","added_by":"auto","created_at":"2025-12-19 17:06:20","extension":"pdf","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":1333867,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Figure\u003c/p\u003e","description":"","filename":"KRASSupplementalFigure20251212.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8370175/v1/473309b1cd473f7d56eab3ec.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Nintedanib inhibits the VEGFR-ERK signaling pathway in human KRAS-mutated cancer cells","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cem\u003eKRAS\u003c/em\u003e mutations play a significant role in the development and progression of various cancers, particularly pancreatic, colorectal, and lung cancers [1,2,3]. The high mutation rate of \u003cem\u003eKRAS\u003c/em\u003e in pancreatic cancer, estimated at 70-90%, correlates with a dismal five-year survival rate of less than 5%, emphasizing the urgent need for more effective therapeutic strategies [2,4,5]. While the EGFR kinase inhibitor erlotinib has received approval as a treatment option, its impact on survival has been limited [5,6,7,8,9]. In colorectal cancer, anti-EGFR monoclonal antibodies have been successfully deployed; however, the presence of RAS mutations severely compromises their efficacy, rendering them ineffective [6,7,10,11]. Similarly, in the context of lung cancer, erlotinib is commercially available for patients with EGFR mutations but has been shown to be ineffective in those with \u003cem\u003eKRAS\u003c/em\u003e mutations [12].\u003c/p\u003e\n\u003cp\u003eIn recent years, however, advancements in drug discovery and deeper understanding of KRAS biology have led to some breakthroughs. For instance, the development of small molecule inhibitors that specifically target \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12C\u003c/sup\u003e mutations has shown promise in preclinical studies and clinical trials. Drugs like sotorasib (AMG 510) and adagrasib (MRTX849) have received attention for their ability to selectively inhibit the G12C variant of KRAS, leading to meaningful clinical responses in patients with tumors harboring this specific mutation [10,11,13,14,15,16,17,]. However, a broader challenge remains because many variants lack defined binding pocket for effective inhibitor binding. As a result, research continues to refine our understanding of RAS biology and to develop innovative therapeutic strategies that effectively target these persistent oncogenic drivers [18,19].\u003c/p\u003e\n\u003cp\u003eGiven the critical role of mutant KRAS in tumorigenesis, there is an urgent need to explore novel therapeutic avenues. Despite the centrality of mutant \u003cem\u003eKRAS\u003c/em\u003e in cancer cell proliferation, the development of direct KRAS inhibitors has faced significant challenges due to the absence of unique structural characteristics that could serve as drug targets [13,20]. Moreover, existing inhibitors targeting downstream signaling or lipid modifications have yielded limited effectiveness [14,21]. From microarray analysis, we found that VEGF signaling molecules are increased in \u003cem\u003eKRAS\u003c/em\u003e mutant cells. Therefore, a deeper understanding of the regulation of KRAS and its upstream signaling molecules, particularly the vascular endothelial growth factor receptor (VEGFR), is necessary. This knowledge could lead to the development of new therapies for cancers associated with \u003cem\u003eKRAS\u003c/em\u003e mutations.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKRAS\u003c/em\u003e mutations play an important role in cell signaling pathways that determine cell proliferation and survival [15,18]. As noted above, mutations typically occur in the GTP-binding pocket, particularly at residues 12, 13, and 61[20, 21, 22]. These mutations inhibit RAS GTPase activity, resulting in a state of sustained activity that continuously signals downstream pathways without the usual regulatory mechanisms provided by RAS GTPase activating protein (GAP) [23]. To further explore the molecular dynamics, it is insightful to refer to the role of the Son of sevenless (SOS) family of guanine nucleotide exchange factors (GEF) that\u0026nbsp;activate RAS by promoting the exchange from the GDP-bound state to the GTP-bound state. [20,24]. Associated with RAS mutations, hyperactive signaling is further exacerbated by enhanced SOS activity and contributes to the oncogenicity of mutant RAS proteins [25]. Studies of SOS1 interaction with its mutant RAS proteins have provided valuable insights into potential therapeutic strategies [26].\u0026nbsp;In our VEGFR2-KO/PL8 \u003cem\u003eKRAS\u003c/em\u003e-mutant cells, inhibition of SOS1 reduced KRAS-GTP activity, leading to decreased phosphorylation of ERK, AKT, and DRP1, and ultimately induced apoptosis.\u003c/p\u003e\n\u003cp\u003eIn our study, we introduced mutation at the G12 position of the KRAS gene in various human somatic cells and myeloma cell lines. This approach aimed to elucidate the altered molecular functions resulting from \u003cem\u003eKRAS\u003c/em\u003e mutations and to identify novel therapeutic targets. Additionally, we screened a library of pharmacological agents and identified nintedanib, an intracellular tyrosine kinase inhibitor, as a potent inhibitor of cell survival in KRAS mutant contexts. Our findings suggest that nintedanib selectively inhibits the proliferation of \u003cem\u003eKRAS\u003c/em\u003e mutant cells, warranting further investigation as a potential candidate for targeted therapy in KRAS-driven malignancies.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEstablishment of KRAS mutant human pancreatic cells\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the role of \u003cem\u003eKRAS\u003c/em\u003e mutations in pancreatic epithelial cells, we generated \u003cem\u003eKRAS\u003c/em\u003e-mutant HPNE cell clones using the CRISPR-Cas9 prime editing system (PE\u003csub\u003emax\u003c/sub\u003e + epegRNAtevopreQ\u003csub\u003e1\u003c/sub\u003e) targeting exon 2 of the KRAS gene in the hTERT-immortalized HPNE cell lines (Fig. 1A). Two \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u0026nbsp;\u003c/sup\u003eknock-in clones and one \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eWT\u003c/sup\u003e control clone were successfully isolated (designated HPNE-\u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D #1\u003c/sup\u003e, HPNE-\u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D #2\u003c/sup\u003e, and HPNE-\u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eWT\u003c/sup\u003e). Sanger sequencing confirmed hetero-allelic G12D knock-in events in the mutant clones (Fig. 1B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eKRAS\u003csup\u003eG12D\u003c/sup\u003e knock-in enhances cell proliferation and clonogenicity in HPNE Cells\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCell growth analysis using the MTT assay revealed significantly enhanced proliferation in \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e clones compared to the parental HPNE and \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eWT\u003c/sup\u003e control cells (Fig. 1C). Furthermore, \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e clones formed a greater number of colonies in soft agar assays relative to control cells (Fig. 1D). Transwell migration assays also indicated a marked increase in migratory capacity in \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e cells (Fig. 1E). These findings underscore the oncogenic potential of \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e in driving proliferation, anchorage-independent growth, and migration in HPNE cells\u003cstrong\u003e\u003cem\u003e.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eKRAS mutation induces the expression of KRAS-related molecules.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ecDNA microarray analysis comparing \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e clones with control cells identified 95 genes upregulated (\u0026gt;5-fold) and 13 genes downregulated (\u0026lt;0.2-fold) in \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e cells (Fig. S1A, Tables S1–S2). Pathway enrichment using Panther Classification Analysis highlighted the activation of cell proliferation pathways such as EGF, FGF, and VEGF signaling (Fig. S1B). Gene Set Enrichment Analysis (GSEA) further confirmed the activation of VEGF_A_UP.V1 and KRAS_DF.V1 oncogenic gene sets in KRAS\u003csup\u003eG12D\u003c/sup\u003e clones (Figs. S2A–S2B). Western blotting validated the elevated expression of VEGF-A in \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u0026nbsp;\u003c/sup\u003ecells relative to KRAS\u003csup\u003eWT\u003c/sup\u003e cells, implicating \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e in modulation of the VEGF-VEGFR axis (Fig. S1C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eScreening of 1,374 pharmacological compounds for selective efficacy in KRAS-mutant cells\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe next performed a drug screening assay using the Selleck L2000 library (catalog number Z295656-384), which contains 1,374 chemical compounds, including known FDA-approved drugs. The screen was conducted using KRAS-mutant cells (\u003cem\u003eKRAS\u003csup\u003eG12A\u003c/sup\u003e\u003c/em\u003e Sachi and \u003cem\u003eKRAS\u003csup\u003eG12D\u003c/sup\u003e\u003c/em\u003e HPNE cell clones) and corresponding KRAS wild-type controls (Sachi and HPNE cells). A summary of the results is provided in Supplementary Table S3. Out of the 1,374 compounds tested, 677 (49%) showed antiproliferative activity in both \u003cem\u003eKRAS\u003csup\u003eG12A\u003c/sup\u003e\u003c/em\u003e Sachi and \u003cem\u003eKRAS\u003csup\u003eG12D\u003c/sup\u003e\u003c/em\u003e HPNE cells compared with \u003cem\u003eKRAS\u003csup\u003eWT\u003c/sup\u003e\u003c/em\u003e counterparts. To identify compounds with selective efficacy in KRAS-mutant cells, we applied a threshold of at least 25% greater viability reduction in mutant versus wild-type cells. Based on this criterion, 34 compounds were identified in \u003cem\u003eKRAS\u003csup\u003eG12A\u003c/sup\u003e\u003c/em\u003e Sachi cells and 205 in \u003cem\u003eKRAS\u003csup\u003eG12D\u003c/sup\u003e\u003c/em\u003e HPNE cells, with six compounds (Nintedanib, Celecoxib, Cediranib, Imatinib Mesylate, Enasidenib, and Gefitinib) common to both cell lines (Fig. 2A). Notably, among the top 10 candidate compounds, three of them (Nintedanib, Cediranib, and Axitinib) -targeting the VEGF signaling pathway (Fig. 2B), highlighting the potential importance of VEGFR inhibition in \u003cem\u003eKRAS\u003c/em\u003e-mutant contexts.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe subsequently examined all VEGF- targeting inhibitors in the library identifying 21 compounds, of which at least 16 showed minimal antiproliferative activity in both of the cell lines (Fig.S3). A detailed summary of their effects on cell viability is provided in Supplementary Table S4.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNintedanib exerts best antiproliferative effects on KRAS mutant cancer cells.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNext, we compared the efficacy of two VEGFR inhibitors identified from our screening nintedanib and axitinib, and included an additional VEGFR inhibitor, motesanib, for evaluation in \u003cem\u003eKRAS\u003c/em\u003e-mutant cell lines. MTT assays and IC₅₀ analyses revealed that nintedanib exhibited the strongest antiproliferative effect against KRAS-mutant cells among the VEGFR inhibitors tested. Notably, nintedanib significantly reduced the cell viability not only in cells with induced \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e and \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12A\u003c/sup\u003e mutations (Sachi, HPNE and HBEC3-KT) (Fig. 2C) but also in several cancer cell lines harboring spontaneous \u003cem\u003eKRAS\u0026nbsp;\u003c/em\u003emutations A549, Lu-99A, DLD-1, Sw-480, PL8, AsPc-1, HCT116, PL5 (Fig. 2D; Table S5).The mean IC\u003csub\u003e50\u003c/sub\u003e value of Nintedanib was approximately 20 μM for \u003cem\u003eKRAS\u003c/em\u003e wild-type cells and 5.0 μM for \u003cem\u003eKRAS\u003c/em\u003e mutant cells (Fig. S4 and Table S5). These results strongly suggest that nintedanib preferentially suppresses the proliferation of \u003cem\u003eKRAS\u003c/em\u003e mutant cancer cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNintedanib\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003epromotes mitochondrial fusion processes and triggers\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;apoptosis in KRAS mutant cell lines\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate the biochemical and molecular mechanisms underlying the action of nintedanib on \u003cem\u003eKRAS\u0026nbsp;\u003c/em\u003emutant cancer cells, we assessed mitochondrial morphology following nintedanib treatment using MitoTracker, a dye that labels functional mitochondria independent of cell viability. Confocal microscopy revealed that nintedanib clearly increased the mitochondrial fusion signals, which were characterized by an elongated tubular network structure, in \u003cem\u003eKRAS\u003c/em\u003e mutant HCT116, PL8, Lu-99A cells (Fig. 3A). We then assessed the effect of nintedanib on the phosphorylation of dynamin-related protein 1 (DRP1), a central mediator of mitochondrial fission. Remarkably, treatment with nintedanib attenuated the phosphorylation of DRP1 in \u003cem\u003eKRAS\u003c/em\u003e mutant cells, suggesting a regulatory effect of nintedanib on mitochondrial fission processes (Fig. 3A and 3B). Western blot analyses further confirmed that nintedanib treatment resulted in reduced phosphorylation levels of several key signaling proteins, including VEGFR1, VEGFR2, ERK, and AKT, (Fig. 3B). Furthermore, the addition of nintedanib to KRAS mutant cell lines (HCT116, PL8, Lu-99A, and HPNE-\u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e) led to a significant increase in the percentage of apoptotic cells, indicating that nintedanib effectively induces apoptosis in these KRAS mutant strains (Fig. 3C). Similarly, the cleaved Caspase3 level was markedly increased in the nintedanib-treated KRAS mutant cells (Fig. 3B). To further explore the mechanism underlying nintedanib-induced apoptosis, we measured intracellular reactive oxygen species (ROS) levels using the DCFH-DA assay. Notably, nintedanib treatment markedly increased ROS production in \u003cem\u003eKRAS\u003c/em\u003e mutant cells (HPNE-\u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e, HCT116, PL8, Lu-99A), whereas ROS levels in \u003cem\u003eKRAS\u003c/em\u003e wild-type cells (HBEC3-KT and HPNE-WT) remained unchanged under both treated and non-treated conditions (Fig. 3D). In summary, our findings suggest that nintedanib selectively induce apoptosis through mitochondrial hyperfusion and increased oxidative stress in \u003cem\u003eKRAS\u003c/em\u003e mutant cells.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eVEGFR2 regulates the activity of KRAS-GTP in the cancer cell line.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo elucidate the role of VEGFR2 on \u003cem\u003eKRAS\u003c/em\u003e-mutated cancer cells, we created VEGFR2 knockout (referred to as VEGFR2-KO/PL8) cell clones #1 and #2 using a KRAS-mutated pancreatic cancer cell line PL8 by targeting exon 20 of the \u003cem\u003eKDR\u003c/em\u003e/\u003cem\u003eVEGFR2\u0026nbsp;\u003c/em\u003egene (Fig. 4A). Sanger sequence and western blot analyses confirmed the successful knockout of \u003cem\u003eVEGFR2\u003c/em\u003e (Figs. 4B and 4C). Western blot analysis revealed that SOS1, RAS-GTP, and the phosphorylation levels of Akt, ERK, and DRP1 readily decrease in \u003cem\u003eVEGFR2\u003c/em\u003e-KO/PL8 cells, compared to those in parental cells. In addition, the protein expression of pro-apoptotic proteins Bax and cleaved caspase-3 increased, while that of anti-apoptotic Bcl2 decreased in the \u003cem\u003eVEGFR2\u003c/em\u003e-KO/PL8 cell clones (Fig. 4C). Furthermore, protein expression of DRP1 clearly decreased in the \u003cem\u003eVEGFR2\u003c/em\u003e-KO/PL8 cells (Figs 4C and 4D). Interestingly, confocal imaging showed a substantial increase in the elongated, tubular mitochondrial structures in the \u003cem\u003eVEGFR2\u003c/em\u003e-KO/KRAS mutant cells, compared to the parental cells (Fig. 4D). To elucidate the involvement of KRAS-GTP on VEGFR2 expression, we introduced exogenous expression of \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e in 293T cells and a mouse fibroblast cell line 3T3 cells. Exogenous \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u003c/sup\u003e clearly increased the expression levels of VEGFR2, suggesting that mutant KRAS\u003csup\u003eG12D\u003c/sup\u003e is inducing phosphorylation of VEGFR2 mediated oncogenic signal (Fig 4E).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eVEGFR2 is preferentially expressed in human pancreatic cancer tissues\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo investigate the expression of VEGFR2 in human pancreatic cancer tissues, we performed immunohistochemical analysis with 80 human pancreatic cancers and 20 normal pancreatic tissues (Table S6 and Fig. 5A). Microscopic analysis detected 1 strong (3+), 35 moderate (2+), and 31 weak (1+) VEGFR2-positive signals in 80 pancreatic cancer tissues, whereas only one moderate and 3 weak signals in 20 normal pancreatic tissues (Table S6 and Figs. 5B- 5C). Accordingly, the positivity rate for VEGFR2 signals in pancreatic cancer tissues (67 of 80 samples; 83%) was significantly higher than that in the normal pancreatic tissues (4 of 20 samples; 20%; Fig. 5D), suggesting that VEGFR-mediated signaling is active in pancreatic cancer tissues.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eNintedanib significantly retards tumor growth in PL8 xenograft mice.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinally, we evaluated the effect of nintedanib on tumor growth in vivo using \u003cem\u003eKRAS\u003c/em\u003e-mutated pancreatic cancer cell line PL8 with immunodeficient nude mice. Of note, administration of nintedanib led to a significant decrease in tumor growth compared to the vehicle control group, as demonstrated in Figs. 6A and 6B. Importantly, treatment with nintedanib did not lead to significant weight losses in mice (Fig. 6C). Moreover, blood chemistry tests revealed that administration of nintedanib did not affect levels of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) (Fig. 6D). These findings support the hypothesis that targeting VEGFR with nintedanib is a viable therapeutic strategy for \u003cem\u003eKRAS\u003c/em\u003e-mutated pancreatic cancers, highlighting its potential as a promising candidate for molecular-targeted anticancer therapies.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cem\u003eKRAS\u003c/em\u003e mutations are frequently observed in several aggressive malignancies, including pancreatic, colorectal, lung, and certain hematological cancers. These mutations leads to constitutive activation of downstream signaling pathways, notably MAPK and PI3K/AKT pathways [27]. Current anti-cancer therapies targeting \u003cem\u003eKRAS\u003c/em\u003e remain limited, largely due to the absence of binding pockets on the KRAS protein, as well as unknown molecular mechanism regulating KRAS-mediated signaling pathway in KRAS mutated tumors. Therefore, the development of novel therapeutic strategies remains a major unmet clinical need [28, 29]. Our findings highlight the potential of nintedanib as a promising candidate for targeting \u003cem\u003eKRAS\u003c/em\u003e-mutated cancers.\u003c/p\u003e\n\u003cp\u003eIn our screening with a large chemical library, nintedanib emerged as a potent agent that selectively inhibits the proliferation of \u003cem\u003eKRAS\u003c/em\u003e-mutant cells. This selectivity is particularly noteworthy, considering that many existing efforts to directly target KRAS have been unsuccessful, largely due to the protein’s \"undruggable\" nature [13]. In this study, we identified one of the upstream signaling components towards KRAS, specifically VEGFR2, as a candidate molecule in our human cell model. \u0026nbsp;Indeed, VEGFR2 plays a pivotal role in maintaining KRAS-mediated oncogenic signaling [25].\u003c/p\u003e\n\u003cp\u003eMTT assays demonstrated that nintedanib exhibits significantly lower IC\u003csub\u003e50\u003c/sub\u003e values in \u003cem\u003eKRAS\u003c/em\u003e-mutant cells compared to their wild-type counterparts, underscoring its selectivity. Importantly, nintedanib demonstrated superior antiproliferative efficacy compared with other VEGFR inhibitors, such as axitinib and motesanib, across various cellular and mutational contexts. Mechanistically, nintedanib suppressed downstream signaling molecules, including pAKT and pERK, indicating thatVEGFR2 inhibition disrupts critical survival and proliferation pathways. Its enhanced efficacy is likely due to broader activity against multiple tyrosine kinases, including FGFRs and PDGFRs, in addition to VEGFR2, which amplifies anti-angiogenic and anti-proliferative effects. Combined with favorable pharmacokinetic properties and dosing advantages, these features likely account for nintedanib’s superior clinical and preclinical performance. \u0026nbsp;Additionally, the induction of apoptosis in \u003cem\u003eKRAS\u003c/em\u003e-mutant cells was accompanied by mitochondrial hyperfusion and elevated ROS, suggesting that nintedanib disrupts mitochondrial homeostasis and redox balance to selectively compromise the survival advantage conferred by mutant\u003cem\u003e\u0026nbsp;KRAS\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eAn intriguing aspect of our study is the regulatory feedback loop identified between KRAS-GTP and VEGFR2 expression. Overexpression of \u003cem\u003eKRAS\u003c/em\u003e\u003csup\u003eG12D\u0026nbsp;\u003c/sup\u003eresulted in elevated VEGFR2 protein levels, suggesting a complex interplay that may contribute to tumor aggressiveness in KRAS-driven cancers [30]. Furthermore, our knock-in cell lines and \u003cem\u003eKRAS\u003c/em\u003e mutant cells demonstrated increased VEGFR2 phosphorylation. Recent reports further support the findings that \u003cem\u003eKRAS\u003c/em\u003e mutations are associated with enhanced VEGFR2 phosphorylation in both tumor vasculature [31] and cancer cells. \u003cem\u003eKRAS\u003c/em\u003e mutations can drive metabolic reprogramming that modulates VEGFR2 activity [32]. Additionally, \u003cem\u003eKRAS\u003c/em\u003e-driven cancers show resistance to anti-VEGF therapies, which correlate with alterations in VEGFR2 signaling pathways [33]. Collectively, these data suggest that \u003cem\u003eKRAS\u003c/em\u003e mutations promote VEGFR2 activation, thereby contributing to tumor angiogenesis and therapy resistance while nintedanib selectively counteracts this process by inducing apoptosis and suppressing tumor growth. Supporting this further, VEGFR2 knockout models using PL8 cells, demonstrated that loss of VEGFR2 decreased in both SOS1 protein level and KRAS-GTP activity, accompanied by reduced AKT-ERK signaling and enhanced apoptosis. The result strongly suggests that VEGFR2 plays a pivotal role in maintaining KRAS activity in \u003cem\u003eKRAS\u003c/em\u003e-mutant cell. Recent evidence indicates that ERK2-dependent phosphorylation of Drp1 plays a critical role in \u003cem\u003eKRAS\u003c/em\u003e-driven tumor growth by facilitating mitochondrial fission, which is essential for metabolic reprogramming and tumor progression, particularly in pancreatic cancer [34,35,36,37]. Inhibition of Drp1 can disrupt glycolytic flux and impair mitochondrial metabolic functions in cells harboring oncogenic \u003cem\u003eKRAS\u003c/em\u003e [38,39,40]. In this study, treatment with nintedanib in \u003cem\u003eKRAS\u003c/em\u003e-mutant cells reduces Drp1 activity and mitochondrial fission in VEGFR2-KO \u003cem\u003eKRAS\u003c/em\u003e-mutant cells. Consistent with these findings, VEGFR2 inhibition by nintedanib suppressed the \u003cem\u003eKRAS\u003c/em\u003e mutation driven increase in mitochondrial fission, suggesting that nintedanib can also block KRAS downstream proliferation signals mediated through mitochondria, highlighting its potential as a highly effective molecular targeted therapy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur immunohistochemical data reveal that VEGFR2 is predominantly expressed in \u003cem\u003eKRAS\u003c/em\u003e-mutant cell lines and patient-derived pancreatic cancer tissues. IHC analysis of human pancreatic cancer samples revealed significantly higher VEGFR2 expression in tumor tissues compared with normal tissue, with an 83% positivity rate suggesting VEGFR2’s involvement in \u003cem\u003eKRAS\u003c/em\u003e-driven oncogenesis and its potential as a biomarker for disease progression and therapeutic targeting.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eIn vivo\u003c/em\u003e, nintedanib significantly inhibited tumor growth in \u003cem\u003eKRAS\u003c/em\u003e mutant xenograft models without notable toxicity, as evidenced by stable body weights and normal liver enzyme levels. These results are promising, as tolerability remains a critical consideration in cancer therapy [8]. Nevertheless, our study has limitations. The reliance on tumor cell lines, cell line-derived xenografts (CDX), and tissue samples restricts the translatability of our findings. Future studies should incorporate patient-derived xenograft (PDX) models, which better recapitulate the tumor microenvironment and heterogeneity, as shown in prior research assessing nintedanib’s efficacy in breast, lung, and pancreatic and kidney cancers [41,42,43,44]. Larger, comprehensive studies are necessary to validate these preliminary findings and establish clinical relevance.\u003c/p\u003e\n\u003cp\u003eIn conclusion, our study identifies nintedanib as a potent therapeutic candidate against \u003cem\u003eKRAS\u003c/em\u003e-mutant cancers by targeting the VEGFR2-ERK signaling axis. The correlation between \u003cem\u003eKRAS\u003c/em\u003e mutations and VEGFR2 expression, supported by molecular and clinical data, suggests VEGFR2 as both a driver and a biomarker of KRAS-driven oncogenesis. Further clinical studies are warranted to assess the utility of nintedanib in treating patients harboring \u003cem\u003eKRAS\u003c/em\u003e mutations.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eCell culture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuman normal epithelial cell lines hTERT-HPNE (CRL-4023) and HBEC3-KT (CRL-4051) were obtained from the American Type Culture Collection (ATCC; Manassas, VA). Additional cell lines, including A549, Lu-99A, DLD1, HCT116, Sw-480, AsPC-1, PL5, and PL8, were generously provided by Dr. Ben Ho Park at Johns Hopkins University (Baltimore, MD). HBEC3-KT cells were cultured in Ham’s F-12 medium supplemented with 10% fetal bovine serum (FBS) and 1% penicillin. In contrast, the remaining cell lines (HPNE, Sachi, A549, Lu-99A, DLD1, HCT116, Sw-480, AsPC-1, PL5, and PL8) were maintained in RPMI-1640 medium (Wako, Osaka, Japan), also supplemented with 10% FBS (Sigma) and 1% penicillin-streptomycin (Wako). All cultures were incubated at 37°C in a humidified atmosphere containing 5% CO\u003csub\u003e2\u003c/sub\u003e. Cells were routinely subcultured upon reaching approximately 80% confluence, maintaining optimal growth conditions. The culture media were changed every 2-3 days, and cell viability and morphology were assessed regularly to ensure healthy growth and proper characteristics of the cell lines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGene Knock-in Using the Prime editing System\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe epegRNA plasmid was constructed utilizing a Golden Gate cloning strategy, involving the assembly of a BsaI-digested epegRNA backbone (pU6-tevopreq1-GG-acceptor, Addgene: #174038) [45,46]. Following digestion, the reaction was incubated at 37°C for 4 hours. Verification of proper digestion was performed using gel electrophoresis, where the expected bands for a correctly digested pegRNA backbone appeared at 2.2 kb. The 2.2 kb fragment was isolated using the Qiagen Gel Extraction Kit. Three annealed double-stranded DNA fragments—comprising the epegRNA spacer sequence, epegRNA scaffold, and epegRNA extension sequence (which includes the PBS and RT template)—were prepared based on the primers listed in Supplementary Table S7. These fragments were mixed and ligated with the epegRNA backbone. To establish a knock-in clone, we transfected 1 µg of the epegRNA G12D plasmid along with the pCMV-PEmax-P2A-GFP (Addgene #180020) plasmid into HPNE and HBEC3-KT cells (1 × 10\u003csup\u003e6\u003c/sup\u003e cells) and using a 4D-Nucleofector instrument (Lonza Japan, Tokyo, Japan). After 3 days post-transfection, GFP-expressing cells were sorted via fluorescence-activated cell sorting (FACS) using a BD FACSAria™ III Cell Single-cell sorting was performed using a BD sorter (BD Biosciences, San Jose, CA, USA). An individual clone was isolated, expanded, and later used for downstream biological assays.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGene Knock-in Using the Crispr Editing System\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe gRNA plasmid was constructed via Golden Gate cloning using BsaI-digested PX458 (Addgene #48138). The backbone was digested at 37°C for 1 hour, purified by Qiagen Gel Extraction, and ligated with an annealed double-stranded gRNA based on primer 5’-AAACTTGTGGTAGTTGGAGC-’. Additionally, a 900 bp exon 2 fragments from RPMI-8226 genomic DNA was amplified and cloned into pcDNA3.1. For knock-in, 1 μg of PX458-RAS gRNA and pcDNA3.1 KRAS\u003csup\u003eG12A\u003c/sup\u003e donor were co-transfected into 1×10\u003csup\u003e6\u003c/sup\u003e Sachi cells via 4D-Nucleofector. After 3 days, GFP-positive cells were sorted by FACS, single clones isolated, expanded, and used for further analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGene knockout using the CRISPR/Cas9 system\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used CRISPR/Cas9 system to knockout VEGFR2 in PL8 cell line, following established procedures [47]. The pSpCas9(BB)-2A-GFP (PX458) plasmid was generously provided by Feng Zhang (plasmid #48138; Addgene, Watertown, MA, USA) [48]. Briefly, sgRNA sequences were chosen using an optimized CRISPR design tool (http://crispr.mit.edu/). The selected sgRNA sequences for VEGFR2 was 5′-GAAACCTGTCCACTTACCTG -3′ in exon 20. Plasmids expressing hCas9 and sgRNA were generated by ligating oligonucleotides into the BbsI site of PX458 (\u003cem\u003eVEGFR2\u003c/em\u003e/PX458). To construct the expression vector KRAS\u003csup\u003eG12D\u003c/sup\u003e, cDNA fragments of KRAS\u003csup\u003eG12D\u003c/sup\u003e was amplified by PCR using Prime STAR Max DNA polymerase (Takara Bio, Otsu, Japan). The cDNA fragments were then introduced into the PiggyBac expression vector (Addgene Cat no #203312). Backbone PiggyBac was used as a control vector. To establish a knockout (KO) clone, 1 μg of \u003cem\u003eVEGFR2\u003c/em\u003e/PX458 plasmid was transfected into the PL8 cell cells (1 × 10\u003csup\u003e6\u003c/sup\u003e cells) using a 4D-Nucleofector instrument (Lonza Japan, Tokyo, Japan). After 3 days, GFP-expressing cells were sorted using fluorescence-activated cell sorting (BD FACSAria™ III Cell Sorter; BD Biosciences, San Jose, CA, USA). A single clone was selected, expanded, and utilized for the biological assays.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell Growth Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCell proliferation was evaluated using the MTT colorimetric assay. Cells were seeded into 96-well plates at a density of 1 × 10³ cells per well and allowed to adhere and grow for predetermined time intervals (0, 24, 48, and 72 hours). At each time point, 10 μl of MTT solution (5 mg/ml; Sigma-Aldrich) was added to each well, followed by incubation at 37°C for 4 hours to enable viable cells to convert MTT into purple formazan crystals. After incubation, the formazan was completely solubilized, and absorbance was measured at 595 nm using a SpectraMAX M5 microplate reader (Molecular Devices, Sunnyvale, CA, USA). The measured optical density (OD) correlated directly with the number of metabolically active cells. All experiments were performed in triplicate, and data are presented as mean ± standard deviation (SD).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWestern Blot Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWestern blot analysis was performed to detect specific proteins in sample extracts as previously established [48,49]. Proteins were first separated by SDS-PAGE, then transferred to a PVDF membrane (Millipore Cat. no IPVH00010), which was blocked with 5% non-fat milk in TBST to minimize non-specific binding. Incubation with primary antibodies (listed in Table S8) occurred overnight at 4°C, followed by washing and application of HRP-conjugated secondary antibodies for 1 hour at room temperature. Immune complexes were detected using ImmunoStar LD chemiluminescent substrate (FUJIFILM Wako Chemicals USA Cat no 292-69903), and bands were visualized with a LAS-4000 image analyzer. Quantification of protein expression levels was conducted using densitometry via ImageJ software, with normalization to GAPDH as a loading control. All experiments were performed in triplicate for reproducibility.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSoft agar colony formation assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe soft agar colony formation assay was carried out as described previous [50, 51]. \u0026nbsp;The number of colonies was counted using Colony Counter software (Keyence, Tokyo, Japan). The data are presented as mean ± SEM (n = 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMigration assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTen thousand cells suspended in 100 μL serum-free medium were added into the upper chambers of a Transwell (8 μm for 24-well plate; Millipore, Tokyo, Japan), as described previously [49] and culture medium was added into the lower chambers. After 24 hours, the cells were fixed by formalin and stained by 0.1% crystal violet. The number of colonies was manually counted under a microscope.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnnexin V assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells were plated into six-well culture plates (5 × 10\u003csup\u003e5\u003c/sup\u003e cells/well) and treated with nintedanib (7.5 µg/mL) for 48 hours. Subsequently, the cells were exposed to annexin V (Ax)-FITC and propidium iodide (PI) (10 μg/mL) at 25°C for 15 minutes. The fluorescence intensities were quantified using fluorescence-activated cell sorting (FACS) analysis (LSRFortessa X-20 Flow Cytometer, BD Biosciences, Franklin Lakes, NJ, USA). [52]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunofluorescence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe cells were cultured on glass coverslips and fixed with a 4% paraformaldehyde solution for 20 minutes at 25°C. Subsequently, the cells were permeabilized with phosphate-buffered saline (PBS) containing 0.1% Triton X-100, blocked in PBS containing 7% serum for 30 minutes, and then incubated with primary antibody (pDRP1) followed by Alexa Fluor-conjugated secondary antibodies (Invitrogen). Cell staining was conducted using MitoTracker (stock solution 1 mM; diluted at 1:10,000) for 1 hour at 37°C to visualize the mitochondria. Following staining, the cells were washed with PBS and fixed with cold paraformaldehyde (3.2% in PBS) for 20 minutes at room temperature. After additional washing steps, the samples were mounted using PermaFluor, and images were captured using the FLUOVIEW FV3000 Series of Confocal Laser Scanning Microscopes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDCFH–DA-based DCF Assay\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCells were seeded into six-well plates at a density of 3 × 10\u003csup\u003e5\u003c/sup\u003e cells per well. After 24 hours, cells were exposed to 5.0 μM nintedanib for one day. Subsequently, cells were incubated with 10 μM DCFH–DA (2’,7’-dichlorodihydrofluorescein diacetate) in culture medium for 45 minutes, protected from light. After incubation, the dye was removed, and cells were washed with PBS. Cells were then trypsinized, collected by centrifugation at 1,000 rpm for 5 minutes, and resuspended in PBS in 0.5-mL tubes on ice. Intracellular ROS levels were assessed by flow cytometry using LSRFortessa X-20 (BD Biosciences). [53]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunohistochemistry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eImmunohistochemical analysis was conducted following previously established protocols [53, 54]. A human Pancreas cancer tissue array (PA1002b; US Biomax, Rockville, MD, USA) was utilized. The tissue sections were treated with primary antibodies against VEGFR2 (2 μg/mL). Negative controls included normal rabbit IgG or omission of the primary antibody. Immunoreactivity was evaluated independently by two investigators (S.K. and H.M.), and staining intensity was scored as strong (3+), moderate (2+), or weak (1+). or negative (0).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ecDNA Microarray Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe cDNA microarray analysis was conducted in accordance with the manufacturer's protocol (Agilent Technologies), as previously described [48]. Briefly, cDNA synthesis and cRNA labeling were performed using cyanine 3 (Cy3) dye with the Agilent Low Input Quick Amp Labeling Kit (Agilent Technologies). The Cy3-labeled cRNA was then purified, fragmented, and hybridized onto a Human Gene Expression 8x60K v2 Microarray Chip, which contains 62,969 Entrez Gene RNAs, utilizing the Agilent Gene Expression Hybridization Kit. Raw and normalized microarray data have been deposited in the Gene Expression Omnibus (GEO) database at the National Center for Biotechnology Information (accession number GSE312012; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE312012). Gene set enrichment analysis was performed according to standard protocols.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eScreening of anticancer drugs library\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA library consisting of 1,374 compounds (Selleck Catalog No. L2000-Z295656, FDA-Approved Drug Library 1300) was screened. Specifically, 500 cells of each of the following lines were seeded into 384-well cell culture plates: Sachi-KRAS\u003csup\u003eWT\u003c/sup\u003e, HPNE-KRAS\u003csup\u003eWT\u003c/sup\u003e, Sachi-KRAS\u003csup\u003eG12A\u003c/sup\u003e, and HPNE-KRAS\u003csup\u003eG12D\u003c/sup\u003e (KRAS gene mutants). The cells were then incubated at 37 °C for 24 hours. Following this, a library of 1,543 compounds was added to each well to achieve a final concentration of 7.5\u0026nbsp;\u0026nbsp;M, and the cells were incubated at 37 °C for an additional 72 hours. After incubation, cell viability was assessed using the MTT assay. The absorbance was measured at 595 nm using a SpectraMAX M5 spectrophotometer (Molecular Devices, Sunnyvale, CA, USA). Control wells containing no drug treatment were considered to have 100% viability, allowing for the calculation of relative cell viability following drug exposure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eXenograft experiments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll animal experiments were conducted in accordance with the protocols (approval number-2022-20) approved by the ethical committee of Aichi Medical University and followed established guidelines. Female Nude mice (BALB/cSlc-nu/nu) (5-week-old, each weighing 14–15 g) were purchased from CLEA Japan, Inc (Tokyo, Japan) and bred at the Institute of Animal Experiments in Aichi Medical University in specified pathogen-free animal facilities. PL8 cells (1 × 10\u003csup\u003e7\u003c/sup\u003e cells) were injected subcutaneously into these mice. When the inoculated tumor reached ~60 mm\u003csup\u003e3\u0026nbsp;\u003c/sup\u003e(day 0), the mice were randomly divided into two groups (treatment and control groups). Nintedanib (15 mg/kg body weight) was intraperitoneally administered on days 0, 3, 5, 7, 9, 11and 13 to each mouse in the treatment group. The control group received PBS as vehicle control. The tumor volume was measured on day 0, 3, 5, 7, 9, 11 and 13 and calculated using the modified ellipsoid formula (1/2 × length × width\u003csup\u003e2\u003c/sup\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBlood chemistry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter two weeks of nintedanib treatment, both control and treatment group mice were anesthetized by isoflurane and about 1 ml of blood were collected in heparin tube. After that blood samples were centrifuged at 800 × g for 20 min for serum collection. Serum was then examined for aspartate aminotransferase (AST) and alanine aminotransferase (ALT) by the Nagahama Life Science Laboratory (Oriental Yeast Co., Ltd., Shiga, Japan).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are expressed as mean ± standard error (SE). Differences among groups were evaluated using one-way analysis of variance (ANOVA) followed by Dunnett’s post hoc test. All statistical analyses were performed using GraphPad Prism and/or SPSS version 23.0 (SPSS Inc., Chicago, IL, USA).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis publication has no conflicts of interest, and there has been no substantial financial support for this work that could have influenced its outcome. The manuscript has been reviewed and endorsed by all named authors, and there are no other individuals who meet the criteria for authorship but are not listed. All authors have consented to the order in which they are listed in the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll accessible data are provided either in the main manuscript or in the supplementary materials. Complete and unaltered western blot data utilized in the study are available in the supplementary information. Furthermore, specific inquiries, data, and materials can be obtained upon reasonable request to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical standards\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was conducted in accordance with the ethical standards set by the Japanese Ministry of Health, Labour, and Welfare. All animal experiments were performed in compliance with the guidelines and regulations of both the Japanese government and Aichi Medical University regarding the care and use of experimental vertebrate animals, with approval from the university’s Animal Care and Use Committee. All recombinant DNA experiments were carried out by certified researchers following appropriate training and were approved by the Recombinant DNA Experiment Safety Committee of Aichi Medical University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConception and design: SK, AO\u003c/p\u003e\n\u003cp\u003eDevelopment of methodology: SK, MNH, AO\u003c/p\u003e\n\u003cp\u003eAcquisition of data/Resources: SK, MNH, NJ, MTAS, MR, HI, YK, YL\u003c/p\u003e\n\u003cp\u003eAnalysis and interpretation of data: SK, MNH, LQM, HM, MW, MLR, TH, SI, TM\u003c/p\u003e\n\u003cp\u003eWriting, review, and/or revision of the manuscript: SK, AO, MNH\u003c/p\u003e\n\u003cp\u003eAdministrative, technical, or material support: YH, TH, HK, ST, IH, SI\u003c/p\u003e\n\u003cp\u003eFunding acquisition: SK, AO\u003c/p\u003e\n\u003cp\u003eStudy supervision: SK\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Dr. Y. Sekido from the Division of Molecular Oncology, Aichi Cancer Center Research Institute, for kindly providing the lung cell line (Lu-99A).This study received partial support from grants provided by the Ministry of Education, Culture, Sports, and Technology of Japan (MEXT, 19K08668, 22K08294 to Y.H., 19K09292, 22K08985, 25K12115 to SK, and 21K08426 to AO), a research grant from the Hori Science and Arts Foundation, and a research grant from the Hirose International Scholarship Foundation (SK). MNH, MTSA and NJ were supported by the Japanese Government (MEXT) Scholarship for Research Student. We would like to thank Takehiko Inaba and Natsumi Kodama at the Institute of Comprehensive Medical Research, Division of Advanced Research Promotion, Aichi Medical University, for their valuable contributions to this investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eUniyal P, Kashyap VK, Behl T, Parashar D, Rawat R. KRAS Mutations in Cancer: Understanding Signaling Pathways to Immune Regulation and the Potential of Immunotherapy. Cancers (Basel). 2025;\u003cstrong\u003e17\u003c/strong\u003e(5).\u003c/li\u003e\n\u003cli\u003eNorton C, Shaw MS, Rubnitz Z, Smith J, Soares HP, Nevala-Plagemann CD, et al. KRAS Mutation Status and Treatment Outcomes in Patients with Metastatic Pancreatic Adenocarcinoma. 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Am J Physiol Cell Physiol. 2025;\u003cstrong\u003e328\u003c/strong\u003e(1):C245-C57.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-8370175/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8370175/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"KRAS mutations are significant drivers in various cancers, and existing drug discovery efforts targeting these mutations have largely been unsuccessful, highlighting the need for more effective therapies. In this study, screening library, which contains 1374 chemical compounds, identified Nintedanib, a VEGFR inhibitor, as having a potent and selective antiproliferative effect against KRAS-mutant cells, surpassing other VEGFR inhibitors. Nintedanib effectively suppressed tumor growth in xenografted mice with KRAS mutations and was found to significantly inhibit phosphorylated VEGFR2 levels and its downstream signaling molecules pAKT and pERK in KRAS-mutant cells, suggesting that VEGFR2 inhibition impacts the oncogenic AKT/ERK pathway. Furthermore, in VEGFR2-knockout cells, KRAS-GTP activity was reduced by inhibiting the SOS1 protein, which led to decreased phosphorylation of ERK, AKT, and DRP1, inducing apoptosis. Notably, overexpression of KRASG12D augmented VEGFR2 expression, establishing a positive feedback loop between KRAS mutations and VEGFR2 signaling within the ERK pathway. Immunohistochemical analyses of pancreatic cancer tissues revealed high VEGFR2 expression in 83% (67/80) of samples, significantly exceeding levels observed in normal pancreatic tissues. These findings highlight VEGFR2 as a promising molecular target and propose a novel therapeutic avenue for KRAS-mutant cancers.","manuscriptTitle":"Nintedanib inhibits the VEGFR-ERK signaling pathway in human KRAS-mutated cancer cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-18 07:32:43","doi":"10.21203/rs.3.rs-8370175/v1","editorialEvents":[],"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":"4a1f9103-2106-4cb1-b9ed-77db56acc21a","owner":[],"postedDate":"December 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59833931,"name":"Biological sciences/Cancer/Cancer therapy/Targeted therapies"},{"id":59833932,"name":"Biological sciences/Drug discovery/Drug screening/Phenotypic screening"}],"tags":[],"updatedAt":"2026-02-04T14:21:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-18 07:32:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8370175","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8370175","identity":"rs-8370175","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}