The Mtor Substrate S6 Kinase 1 (S6K1)
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Gene Symbol Gene Description ACVR1B Activin a Receptor, Type IB
Table S1. Kinase clones included in human kinase cDNA library for yeast two-hybrid screening Gene Symbol Gene Description ACVR1B activin A receptor, type IB ADCK2 aarF domain containing kinase 2 ADCK4 aarF domain containing kinase 4 AGK multiple substrate lipid kinase;MULK AK1 adenylate kinase 1 AK3 adenylate kinase 3 like 1 AK3L1 adenylate kinase 3 ALDH18A1 aldehyde dehydrogenase 18 family, member A1;ALDH18A1 ALK anaplastic lymphoma kinase (Ki-1) ALPK1 alpha-kinase 1 ALPK2 alpha-kinase 2 AMHR2 anti-Mullerian hormone receptor, type II ARAF v-raf murine sarcoma 3611 viral oncogene homolog 1 ARSG arylsulfatase G;ARSG AURKB aurora kinase B AURKC aurora kinase C BCKDK branched chain alpha-ketoacid dehydrogenase kinase BMPR1A bone morphogenetic protein receptor, type IA BMPR2 bone morphogenetic protein receptor, type II (serine/threonine kinase) BRAF v-raf murine sarcoma viral oncogene homolog B1 BRD3 bromodomain containing 3 BRD4 bromodomain containing 4 BTK Bruton agammaglobulinemia tyrosine kinase BUB1 BUB1 budding uninhibited by benzimidazoles 1 homolog (yeast) BUB1B BUB1 budding uninhibited by benzimidazoles 1 homolog beta (yeast) C9orf98 chromosome 9 open reading frame 98;C9orf98 CABC1 chaperone, ABC1 activity of bc1 complex like (S. pombe) CALM1 calmodulin 1 (phosphorylase kinase, delta) CALM2 calmodulin 2 (phosphorylase kinase, delta) CALM3 calmodulin 3 (phosphorylase kinase, delta) CAMK1 calcium/calmodulin-dependent protein kinase I CAMK2A calcium/calmodulin-dependent protein kinase (CaM kinase) II alpha CAMK2B calcium/calmodulin-dependent -
Aberrant Modulation of Ribosomal Protein S6 Phosphorylation Confers Acquired Resistance to MAPK Pathway Inhibitors in BRAF-Mutant Melanoma
www.nature.com/aps ARTICLE Aberrant modulation of ribosomal protein S6 phosphorylation confers acquired resistance to MAPK pathway inhibitors in BRAF-mutant melanoma Ming-zhao Gao1,2, Hong-bin Wang1,2, Xiang-ling Chen1,2, Wen-ting Cao1,LiFu1, Yun Li1, Hai-tian Quan1,2, Cheng-ying Xie1,2 and Li-guang Lou1,2 BRAF and MEK inhibitors have shown remarkable clinical efficacy in BRAF-mutant melanoma; however, most patients develop resistance, which limits the clinical benefit of these agents. In this study, we found that the human melanoma cell clones, A375-DR and A375-TR, with acquired resistance to BRAF inhibitor dabrafenib and MEK inhibitor trametinib, were cross resistant to other MAPK pathway inhibitors. In these resistant cells, phosphorylation of ribosomal protein S6 (rpS6) but not phosphorylation of ERK or p90 ribosomal S6 kinase (RSK) were unable to be inhibited by MAPK pathway inhibitors. Notably, knockdown of rpS6 in these cells effectively downregulated G1 phase-related proteins, including RB, cyclin D1, and CDK6, induced cell cycle arrest, and inhibited proliferation, suggesting that aberrant modulation of rpS6 phosphorylation contributed to the acquired resistance. Interestingly, RSK inhibitor had little effect on rpS6 phosphorylation and cell proliferation in resistant cells, whereas P70S6K inhibitor showed stronger inhibitory effects on rpS6 phosphorylation and cell proliferation in resistant cells than in parental cells. Thus regulation of rpS6 phosphorylation, which is predominantly mediated by BRAF/MEK/ERK/RSK signaling in parental cells, was switched to mTOR/ P70S6K signaling in resistant cells. Furthermore, mTOR inhibitors alone overcame acquired resistance and rescued the sensitivity of the resistant cells when combined with BRAF/MEK inhibitors. -
Human Melanoma Cells Resistant to MAPK Inhibitors Can Be Effectively Targeted by Inhibition of the P90 Ribosomal S6 Kinase
www.impactjournals.com/oncotarget/ Oncotarget, 2017, Vol. 8, (No. 22), pp: 35761-35775 Research Paper Human melanoma cells resistant to MAPK inhibitors can be effectively targeted by inhibition of the p90 ribosomal S6 kinase Corinna Kosnopfel1, Tobias Sinnberg1, Birgit Sauer1, Heike Niessner1, Anja Schmitt2, Elena Makino1, Andrea Forschner1, Stephan Hailfinger2, Claus Garbe1, Birgit Schittek1 1Division of Dermatooncology, Department of Dermatology, University of Tübingen, Tübingen, Germany 2Interfaculty Institute of Biochemistry, University of Tübingen, Tübingen, Germany Correspondence to: Birgit Schittek, email: [email protected] Keywords: melanoma, MAPK inhibition, therapy resistance, p90 ribosomal S6 kinase, YB-1 Received: January 18, 2017 Accepted: March 06, 2017 Published: March 15, 2017 Copyright: Kosnopfel et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT The clinical availability of small molecule inhibitors specifically targeting mutated BRAF marked a significant breakthrough in melanoma therapy. Despite a dramatic anti-tumour activity and improved patient survival, rapidly emerging resistance, however, greatly limits the clinical benefit. The majority of the already described resistance mechanisms involve a reactivation of the MAPK signalling pathway. The p90 ribosomal S6 kinase (RSK), a downstream effector of the MAPK signalling cascade, has been reported to enhance survival of melanoma cells in response to chemotherapy. Here, we can show that RSK activity is significantly increased in human melanoma cells with acquired resistance to the BRAFV600E/K inhibitor vemurafenib. Interestingly, inhibition of RSK signalling markedly impairs the viability of vemurafenib resistant melanoma cells and is effective both in two-dimensional and in three-dimensional culture systems, especially in a chronic, long-term application. -
Supplementary Table S1. Upregulated Genes Differentially
Supplementary Table S1. Upregulated genes differentially expressed in athletes (p < 0.05 and 1.3-fold change) Gene Symbol p Value Fold Change 221051_s_at NMRK2 0.01 2.38 236518_at CCDC183 0.00 2.05 218804_at ANO1 0.00 2.05 234675_x_at 0.01 2.02 207076_s_at ASS1 0.00 1.85 209135_at ASPH 0.02 1.81 228434_at BTNL9 0.03 1.81 229985_at BTNL9 0.01 1.79 215795_at MYH7B 0.01 1.78 217979_at TSPAN13 0.01 1.77 230992_at BTNL9 0.01 1.75 226884_at LRRN1 0.03 1.74 220039_s_at CDKAL1 0.01 1.73 236520_at 0.02 1.72 219895_at TMEM255A 0.04 1.72 201030_x_at LDHB 0.00 1.69 233824_at 0.00 1.69 232257_s_at 0.05 1.67 236359_at SCN4B 0.04 1.64 242868_at 0.00 1.63 1557286_at 0.01 1.63 202780_at OXCT1 0.01 1.63 1556542_a_at 0.04 1.63 209992_at PFKFB2 0.04 1.63 205247_at NOTCH4 0.01 1.62 1554182_at TRIM73///TRIM74 0.00 1.61 232892_at MIR1-1HG 0.02 1.61 204726_at CDH13 0.01 1.6 1561167_at 0.01 1.6 1565821_at 0.01 1.6 210169_at SEC14L5 0.01 1.6 236963_at 0.02 1.6 1552880_at SEC16B 0.02 1.6 235228_at CCDC85A 0.02 1.6 1568623_a_at SLC35E4 0.00 1.59 204844_at ENPEP 0.00 1.59 1552256_a_at SCARB1 0.02 1.59 1557283_a_at ZNF519 0.02 1.59 1557293_at LINC00969 0.03 1.59 231644_at 0.01 1.58 228115_at GAREM1 0.01 1.58 223687_s_at LY6K 0.02 1.58 231779_at IRAK2 0.03 1.58 243332_at LOC105379610 0.04 1.58 232118_at 0.01 1.57 203423_at RBP1 0.02 1.57 AMY1A///AMY1B///AMY1C///AMY2A///AMY2B// 208498_s_at 0.03 1.57 /AMYP1 237154_at LOC101930114 0.00 1.56 1559691_at 0.01 1.56 243481_at RHOJ 0.03 1.56 238834_at MYLK3 0.01 1.55 213438_at NFASC 0.02 1.55 242290_at TACC1 0.04 1.55 ANKRD20A1///ANKRD20A12P///ANKRD20A2/// -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
The Role of the S6K2 Splice Isoform in Mtor/S6K Signalling and Cellular Functions
The role of the S6K2 splice isoform in mTOR/S6K signalling and cellular functions Olena Myronova A thesis submitted to the University College London in fulfilment with the requirements for the degree of Doctor of Philosophy London, November 2015 Research Department of Structural and Molecular Biology Division of Biosciences University College London Gower Street London, WC1E 6BT United Kingdom Ludwig Institute for Cancer Research 666 Third Avenue, 28th floor New York, N.Y. 10017 USA The role of the S6K2 splice isoform in mTOR/S6K signalling and cellular functions 1 Declaration I, Olena Myronova, declare that all the work presented in this thesis is the result of my own work. The work presented here does not constitute part of any other thesis. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. The work here in was carried out while I was a graduate research student at University College London, Research Department of Structural and Molecular Biology under the supervision of Professor Ivan Gout. Olena Myronova The role of the S6K2 splice isoform in mTOR/S6K signalling and cellular functions 2 Abstract Ribosomal S6 kinase (S6K) is a member of the AGC family of serine/threonine protein kinases and plays a key role in diverse cellular processes, including cell growth, survival and metabolism. Activation of S6K by growth factors, amino acids, energy levels and hypoxia is mediated by the mTOR and PI3K signalling pathways. Dysregulation of S6K activity has been implicated in a number of human pathologies, including cancer, diabetes, obesity and ageing. -
Mouse Rps6ka5 Antibody (C-Term) Purified Rabbit Polyclonal Antibody (Pab) Catalog # AW5466
10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 Mouse Rps6ka5 Antibody (C-term) Purified Rabbit Polyclonal Antibody (Pab) Catalog # AW5466 Specification Mouse Rps6ka5 Antibody (C-term) - Product Information Application WB,E Primary Accession Q8C050 Reactivity Mouse Host Rabbit Clonality Polyclonal Calculated MW M=97,90 KDa Isotype Rabbit Ig Antigen Source HUMAN Mouse Rps6ka5 Antibody (C-term) - Additional Information Gene ID 73086 Antigen Region All lanes : Anti-Rps6ka5 Antibody (C-term) at 850-883 1:1000 dilution Lane 1: L929 whole cell Other Names lysates Lane 2: mouse spleen lysates Lane 3: Ribosomal protein S6 kinase alpha-5, mouse thymus lysates Lysates/proteins at 20 S6K-alpha-5, 90 kDa ribosomal protein S6 µg per lane. Secondary Goat Anti-Rabbit IgG, kinase 5, Nuclear mitogen- and (H+L),Peroxidase conjugated at 1/10000 stress-activated protein kinase 1, RSK-like dilution Predicted band size : 97 kDa protein kinase, RLSK, Rps6ka5, Msk1 Blocking/Dilution buffer: 5% NFDM/TBST. Dilution WB~~1:1000 Mouse Rps6ka5 Antibody (C-term) - Background Target/Specificity This Mouse Rps6ka5 antibody is generated Serine/threonine-protein kinase that is from a rabbit immunized with a KLH required for the mitogen or stress-induced conjugated synthetic peptide between phosphorylation of the transcription factors 850-883 amino acids from the C-terminal CREB1 and ATF1 and for the regulation of the region of Mouse Rps6ka5. transcription factors RELA, STAT3 and ETV1/ER81, and that contributes to gene Format activation by histone phosphorylation and Purified polyclonal antibody supplied in PBS functions in the regulation of inflammatory with 0.09% (W/V) sodium azide. -
Phospho-RPS6KA5-T581 Rabbit Pab
Leader in Biomolecular Solutions for Life Science Phospho-RPS6KA5-T581 Rabbit pAb Catalog No.: AP1197 Basic Information Background Catalog No. Serine/threonine-protein kinase that is required for the mitogen or stress-induced AP1197 phosphorylation of the transcription factors CREB1 and ATF1 and for the regulation of the transcription factors RELA, STAT3 and ETV1/ER81, and that contributes to gene Observed MW activation by histone phosphorylation and functions in the regulation of inflammatory Refer to figures genes (PubMed:11909979, PubMed:12569367, PubMed:12763138, PubMed:9687510, PubMed:18511904, PubMed:9873047). Phosphorylates CREB1 and ATF1 in response to Calculated MW mitogenic or stress stimuli such as UV-C irradiation, epidermal growth factor (EGF) and 61kDa/81kDa/89kDa anisomycin (PubMed:11909979, PubMed:9873047). Plays an essential role in the control of RELA transcriptional activity in response to TNF and upon glucocorticoid, associates in Category the cytoplasm with the glucocorticoid receptor NR3C1 and contributes to RELA inhibition and repression of inflammatory gene expression (PubMed:12628924, Primary antibody PubMed:18511904). In skeletal myoblasts is required for phosphorylation of RELA at 'Ser-276' during oxidative stress (PubMed:12628924). In erythropoietin-stimulated cells, Applications is necessary for the 'Ser-727' phosphorylation of STAT3 and regulation of its WB transcriptional potential (PubMed:12763138). Phosphorylates ETV1/ER81 at 'Ser-191' and 'Ser-216', and thereby regulates its ability to stimulate transcription, which may be Cross-Reactivity important during development and breast tumor formation (PubMed:12569367). Directly Human, Mouse, Rat represses transcription via phosphorylation of 'Ser-1' of histone H2A (PubMed:15010469). Phosphorylates 'Ser-10' of histone H3 in response to mitogenics, stress stimuli and EGF, which results in the transcriptional activation of several Recommended Dilutions immediate early genes, including proto-oncogenes c-fos/FOS and c-jun/JUN (PubMed:12773393). -
Profiling Data
Compound Name DiscoveRx Gene Symbol Entrez Gene Percent Compound Symbol Control Concentration (nM) JNK-IN-8 AAK1 AAK1 69 1000 JNK-IN-8 ABL1(E255K)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317I)-nonphosphorylated ABL1 87 1000 JNK-IN-8 ABL1(F317I)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317L)-nonphosphorylated ABL1 65 1000 JNK-IN-8 ABL1(F317L)-phosphorylated ABL1 61 1000 JNK-IN-8 ABL1(H396P)-nonphosphorylated ABL1 42 1000 JNK-IN-8 ABL1(H396P)-phosphorylated ABL1 60 1000 JNK-IN-8 ABL1(M351T)-phosphorylated ABL1 81 1000 JNK-IN-8 ABL1(Q252H)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(Q252H)-phosphorylated ABL1 56 1000 JNK-IN-8 ABL1(T315I)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(T315I)-phosphorylated ABL1 92 1000 JNK-IN-8 ABL1(Y253F)-phosphorylated ABL1 71 1000 JNK-IN-8 ABL1-nonphosphorylated ABL1 97 1000 JNK-IN-8 ABL1-phosphorylated ABL1 100 1000 JNK-IN-8 ABL2 ABL2 97 1000 JNK-IN-8 ACVR1 ACVR1 100 1000 JNK-IN-8 ACVR1B ACVR1B 88 1000 JNK-IN-8 ACVR2A ACVR2A 100 1000 JNK-IN-8 ACVR2B ACVR2B 100 1000 JNK-IN-8 ACVRL1 ACVRL1 96 1000 JNK-IN-8 ADCK3 CABC1 100 1000 JNK-IN-8 ADCK4 ADCK4 93 1000 JNK-IN-8 AKT1 AKT1 100 1000 JNK-IN-8 AKT2 AKT2 100 1000 JNK-IN-8 AKT3 AKT3 100 1000 JNK-IN-8 ALK ALK 85 1000 JNK-IN-8 AMPK-alpha1 PRKAA1 100 1000 JNK-IN-8 AMPK-alpha2 PRKAA2 84 1000 JNK-IN-8 ANKK1 ANKK1 75 1000 JNK-IN-8 ARK5 NUAK1 100 1000 JNK-IN-8 ASK1 MAP3K5 100 1000 JNK-IN-8 ASK2 MAP3K6 93 1000 JNK-IN-8 AURKA AURKA 100 1000 JNK-IN-8 AURKA AURKA 84 1000 JNK-IN-8 AURKB AURKB 83 1000 JNK-IN-8 AURKB AURKB 96 1000 JNK-IN-8 AURKC AURKC 95 1000 JNK-IN-8 -
Application of a MYC Degradation
SCIENCE SIGNALING | RESEARCH ARTICLE CANCER Copyright © 2019 The Authors, some rights reserved; Application of a MYC degradation screen identifies exclusive licensee American Association sensitivity to CDK9 inhibitors in KRAS-mutant for the Advancement of Science. No claim pancreatic cancer to original U.S. Devon R. Blake1, Angelina V. Vaseva2, Richard G. Hodge2, McKenzie P. Kline3, Thomas S. K. Gilbert1,4, Government Works Vikas Tyagi5, Daowei Huang5, Gabrielle C. Whiten5, Jacob E. Larson5, Xiaodong Wang2,5, Kenneth H. Pearce5, Laura E. Herring1,4, Lee M. Graves1,2,4, Stephen V. Frye2,5, Michael J. Emanuele1,2, Adrienne D. Cox1,2,6, Channing J. Der1,2* Stabilization of the MYC oncoprotein by KRAS signaling critically promotes the growth of pancreatic ductal adeno- carcinoma (PDAC). Thus, understanding how MYC protein stability is regulated may lead to effective therapies. Here, we used a previously developed, flow cytometry–based assay that screened a library of >800 protein kinase inhibitors and identified compounds that promoted either the stability or degradation of MYC in a KRAS-mutant PDAC cell line. We validated compounds that stabilized or destabilized MYC and then focused on one compound, Downloaded from UNC10112785, that induced the substantial loss of MYC protein in both two-dimensional (2D) and 3D cell cultures. We determined that this compound is a potent CDK9 inhibitor with a previously uncharacterized scaffold, caused MYC loss through both transcriptional and posttranslational mechanisms, and suppresses PDAC anchorage- dependent and anchorage-independent growth. We discovered that CDK9 enhanced MYC protein stability 62 through a previously unknown, KRAS-independent mechanism involving direct phosphorylation of MYC at Ser . -
In Vitro Pharmacological Profiling of R406 Identifies Molecular Targets
ORIGINAL ARTICLE In vitro pharmacological profiling of R406 identifies molecular targets underlying the clinical effects of fostamatinib Michael G. Rolf, Jon O. Curwen, Margaret Veldman-Jones, Cath Eberlein, Jianyan Wang, Alex Harmer, Caroline J. Hellawell & Martin Braddock AstraZeneca R&D Alderley Park, Macclesfield, Cheshire SK10 4TG, United Kingdom Keywords Abstract Blood pressure elevation, fostamatinib, in vitro pharmacological profiling, R406, SYK Off-target pharmacology may contribute to both adverse and beneficial effects of a new drug. In vitro pharmacological profiling is often applied early in drug Correspondence discovery; there are fewer reports addressing the relevance of broad profiles to Michael G. Rolf, AstraZeneca R&D Molndal,€ clinical adverse effects. Here, we have characterized the pharmacological profile Pepparedsleden 1, 431 83 Mo¨ lndal, Sweden. of the active metabolite of fostamatinib, R406, linking an understanding of drug Tel: +46 31 776 60 40; Fax: +46 31 776 37 selectivity to the increase in blood pressure observed in clinical studies. R406 60; E-mail: [email protected] was profiled in a broad range of in vitro assays to generate a comprehensive Funding Information pharmacological profile and key targets were further investigated using func- No funding information provided. tional and cellular assay systems. A combination of traditional literature searches and text-mining approaches established potential mechanistic links Received: 9 April 2015; Accepted: 14 July between the profile of R406 and clinical side effects. R406 was selective outside 2015 the kinase domain, with only antagonist activity at the adenosine A3 receptor in the range relevant to clinical effects. R406 was less selective in the kinase Pharma Res Per, 3(5), 2015, e00175, doi: 10.1002/prp2.175 domain, having activity at many protein kinases at therapeutically relevant con- centrations when tested in multiple in vitro systems. -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1.