Comparative Analysis of Protein Expression Concomitant with DNA Methyltransferase 3A Depletion in a Melanoma Cell Line
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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 -
Anti-SEK1 / MKK4 Phospho (Ser80) Antibody (ARG51673)
Product datasheet [email protected] ARG51673 Package: 100 μl, 50 μl anti-SEK1 / MKK4 phospho (Ser80) antibody Store at: -20°C Summary Product Description Rabbit Polyclonal antibody recognizes SEK1 / MKK4 phospho (Ser80) Tested Reactivity Hu, Ms, Rat Tested Application ICC/IF, IHC-P, WB Host Rabbit Clonality Polyclonal Isotype IgG Target Name SEK1 / MKK4 Antigen Species Human Immunogen Peptide sequence around phosphorylation site of serine 80 (T-H-S(p)-I-E) derived from Human SEK1/MKK4. Conjugation Un-conjugated Alternate Names MEK 4; MAPK/ERK kinase 4; PRKMK4; SAPKK-1; SAPK/ERK kinase 1; SKK1; JNK-activating kinase 1; EC 2.7.12.2; MEK4; MAP kinase kinase 4; c-Jun N-terminal kinase kinase 1; SEK1; SAPKK1; MAPKK4; Stress- activated protein kinase kinase 1; JNKK1; MKK4; SERK1; SAPK kinase 1; Dual specificity mitogen- activated protein kinase kinase 4; JNKK; MAPKK 4 Application Instructions Application table Application Dilution ICC/IF 1:100 - 1:200 IHC-P 1:50 - 1:100 WB 1:500 - 1:1000 Application Note * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Calculated Mw 44 kDa Properties Form Liquid Purification Antibodies were produced by immunizing rabbits with KLH-conjugated synthetic phosphopeptide. Antibodies were purified by affinity-chromatography using epitope-specific phosphopeptide. In addition, non-phospho specific antibodies were removed by chromatogramphy using non- phosphopeptide. Buffer PBS (without Mg2+ and Ca2+, pH 7.4), 150mM NaCl, 0.02% Sodium azide and 50% Glycerol. Preservative 0.02% Sodium azide Stabilizer 50% Glycerol www.arigobio.com 1/3 Concentration 1 mg/ml Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. -
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 . -
Modulation of NF-Κb Signalling by Microbial Pathogens
REVIEWS Modulation of NF‑κB signalling by microbial pathogens Masmudur M. Rahman and Grant McFadden Abstract | The nuclear factor-κB (NF‑κB) family of transcription factors plays a central part in the host response to infection by microbial pathogens, by orchestrating the innate and acquired host immune responses. The NF‑κB proteins are activated by diverse signalling pathways that originate from many different cellular receptors and sensors. Many successful pathogens have acquired sophisticated mechanisms to regulate the NF‑κB signalling pathways by deploying subversive proteins or hijacking the host signalling molecules. Here, we describe the mechanisms by which viruses and bacteria micromanage the host NF‑κB signalling circuitry to favour the continued survival of the pathogen. The nuclear factor-κB (NF-κB) family of transcription Signalling targets upstream of NF‑κB factors regulates the expression of hundreds of genes that NF-κB proteins are tightly regulated in both the cyto- are associated with diverse cellular processes, such as pro- plasm and the nucleus6. Under normal physiological liferation, differentiation and death, as well as innate and conditions, NF‑κB complexes remain inactive in the adaptive immune responses. The mammalian NF‑κB cytoplasm through a direct interaction with proteins proteins are members of the Rel domain-containing pro- of the inhibitor of NF-κB (IκB) family, including IκBα, tein family: RELA (also known as p65), RELB, c‑REL, IκBβ and IκBε (also known as NF-κBIα, NF-κBIβ and the NF-κB p105 subunit (also known as NF‑κB1; which NF-κBIε, respectively); IκB proteins mask the nuclear is cleaved into the p50 subunit) and the NF-κB p100 localization domains in the NF‑κB complex, thus subunit (also known as NF‑κB2; which is cleaved into retaining the transcription complex in the cytoplasm. -
Supplementary Table 1
SI Table S1. Broad protein kinase selectivity for PF-2771. Kinase, PF-2771 % Inhibition at 10 μM Service Kinase, PF-2771 % Inhibition at 1 μM Service rat RPS6KA1 (RSK1) 39 Dundee AURKA (AURA) 24 Invitrogen IKBKB (IKKb) 26 Dundee CDK2 /CyclinA 21 Invitrogen mouse LCK 25 Dundee rabbit MAP2K1 (MEK1) 19 Dundee AKT1 (AKT) 21 Dundee IKBKB (IKKb) 16 Dundee CAMK1 (CaMK1a) 19 Dundee PKN2 (PRK2) 14 Dundee RPS6KA5 (MSK1) 18 Dundee MAPKAPK5 14 Dundee PRKD1 (PKD1) 13 Dundee PIM3 12 Dundee MKNK2 (MNK2) 12 Dundee PRKD1 (PKD1) 12 Dundee MARK3 10 Dundee NTRK1 (TRKA) 12 Invitrogen SRPK1 9 Dundee MAPK12 (p38g) 11 Dundee MAPKAPK5 9 Dundee MAPK8 (JNK1a) 11 Dundee MAPK13 (p38d) 8 Dundee rat PRKAA2 (AMPKa2) 11 Dundee AURKB (AURB) 5 Dundee NEK2 11 Invitrogen CSK 5 Dundee CHEK2 (CHK2) 11 Invitrogen EEF2K (EEF-2 kinase) 4 Dundee MAPK9 (JNK2) 9 Dundee PRKCA (PKCa) 4 Dundee rat RPS6KA1 (RSK1) 8 Dundee rat PRKAA2 (AMPKa2) 4 Dundee DYRK2 7 Dundee rat CSNK1D (CKId) 3 Dundee AKT1 (AKT) 7 Dundee LYN 3 BioPrint PIM2 7 Invitrogen CSNK2A1 (CKIIa) 3 Dundee MAPK15 (ERK7) 6 Dundee CAMKK2 (CAMKKB) 1 Dundee mouse LCK 5 Dundee PIM3 1 Dundee PDPK1 (PDK1) (directed 5 Invitrogen rat DYRK1A (MNB) 1 Dundee RPS6KB1 (p70S6K) 5 Dundee PBK 0 Dundee CSNK2A1 (CKIIa) 4 Dundee PIM1 -1 Dundee CAMKK2 (CAMKKB) 4 Dundee DYRK2 -2 Dundee SRC 4 Invitrogen MAPK12 (p38g) -2 Dundee MYLK2 (MLCK_sk) 3 Invitrogen NEK6 -3 Dundee MKNK2 (MNK2) 2 Dundee RPS6KB1 (p70S6K) -3 Dundee SRPK1 2 Dundee AKT2 -3 Dundee MKNK1 (MNK1) 2 Dundee RPS6KA3 (RSK2) -3 Dundee CHEK1 (CHK1) 2 Invitrogen rabbit MAP2K1 (MEK1) -4 Dundee -
Deep Multiomics Profiling of Brain Tumors Identifies Signaling Networks
ARTICLE https://doi.org/10.1038/s41467-019-11661-4 OPEN Deep multiomics profiling of brain tumors identifies signaling networks downstream of cancer driver genes Hong Wang 1,2,3, Alexander K. Diaz3,4, Timothy I. Shaw2,5, Yuxin Li1,2,4, Mingming Niu1,4, Ji-Hoon Cho2, Barbara S. Paugh4, Yang Zhang6, Jeffrey Sifford1,4, Bing Bai1,4,10, Zhiping Wu1,4, Haiyan Tan2, Suiping Zhou2, Laura D. Hover4, Heather S. Tillman 7, Abbas Shirinifard8, Suresh Thiagarajan9, Andras Sablauer 8, Vishwajeeth Pagala2, Anthony A. High2, Xusheng Wang 2, Chunliang Li 6, Suzanne J. Baker4 & Junmin Peng 1,2,4 1234567890():,; High throughput omics approaches provide an unprecedented opportunity for dissecting molecular mechanisms in cancer biology. Here we present deep profiling of whole proteome, phosphoproteome and transcriptome in two high-grade glioma (HGG) mouse models driven by mutated RTK oncogenes, PDGFRA and NTRK1, analyzing 13,860 proteins and 30,431 phosphosites by mass spectrometry. Systems biology approaches identify numerous master regulators, including 41 kinases and 23 transcription factors. Pathway activity computation and mouse survival indicate the NTRK1 mutation induces a higher activation of AKT down- stream targets including MYC and JUN, drives a positive feedback loop to up-regulate multiple other RTKs, and confers higher oncogenic potency than the PDGFRA mutation. A mini-gRNA library CRISPR-Cas9 validation screening shows 56% of tested master regulators are important for the viability of NTRK-driven HGG cells, including TFs (Myc and Jun) and metabolic kinases (AMPKa1 and AMPKa2), confirming the validity of the multiomics inte- grative approaches, and providing novel tumor vulnerabilities. -
Characterization of the Small Molecule Kinase Inhibitor SU11248 (Sunitinib/ SUTENT in Vitro and in Vivo
TECHNISCHE UNIVERSITÄT MÜNCHEN Lehrstuhl für Genetik Characterization of the Small Molecule Kinase Inhibitor SU11248 (Sunitinib/ SUTENT in vitro and in vivo - Towards Response Prediction in Cancer Therapy with Kinase Inhibitors Michaela Bairlein Vollständiger Abdruck der von der Fakultät Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt der Technischen Universität München zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften genehmigten Dissertation. Vorsitzender: Univ. -Prof. Dr. K. Schneitz Prüfer der Dissertation: 1. Univ.-Prof. Dr. A. Gierl 2. Hon.-Prof. Dr. h.c. A. Ullrich (Eberhard-Karls-Universität Tübingen) 3. Univ.-Prof. A. Schnieke, Ph.D. Die Dissertation wurde am 07.01.2010 bei der Technischen Universität München eingereicht und durch die Fakultät Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt am 19.04.2010 angenommen. FOR MY PARENTS 1 Contents 2 Summary ................................................................................................................................................................... 5 3 Zusammenfassung .................................................................................................................................................... 6 4 Introduction .............................................................................................................................................................. 8 4.1 Cancer .............................................................................................................................................................. -
A Novel JAK1 Mutant Breast Implant-Associated Anaplastic Large Cell Lymphoma Patient-Derived Xenograft Fostering Pre- Clinical Discoveries
Cancers 2019 S1 of S18 Supplementary Materials: A Novel JAK1 Mutant Breast Implant-Associated Anaplastic Large Cell Lymphoma Patient-Derived Xenograft Fostering Pre- Clinical Discoveries Danilo Fiore, Luca Vincenzo Cappelli, Paul Zumbo, Jude M. Phillip, Zhaoqi Liu, Shuhua Cheng, Liron Yoffe, Paola Ghione, Federica Di Maggio, Ahmet Dogan, Inna Khodos, Elisa de Stanchina, Joseph Casano, Clarisse Kayembe, Wayne Tam, Doron Betel, Robin Foa’, Leandro Cerchietti, Raul Rabadan, Steven Horwitz, David M. Weinstock and Giorgio Inghirami A B C Figure S1. (A) Histology micrografts on IL89 PDTX show overall similarity between T1 T3 and T7 passages (upper panels). Immunohistochemical stains with the indicated antibodies (anti-CD3, anti- CD25 and anti-CD8 [x20]) (lower panels). (B) Flow cytometry panel comprehensive of the most represented surface T-cell lymphoma markers, including: CD2, CD3, CD4, CD5, CD8, CD16, CD25, CD30, CD56, TCRab, TCRgd. IL89 PDTX passage T3 is here depicted for illustration purposes. (C) Analysis of the TCR gamma specific rearrangement clonality in IL89 diagnostic sample and correspondent PDTX after 1 and 5 passages (T1 and T5). A WT Primary p.G1097D IL89 T1 p.G1097D IL89 T5 p.G1097D IL89 cell line B Figure S2. (A) Sanger sequencing confirms the presence of the JAK1 p.G1097D mutation in IL89 PDTX samples and in the cell line, but the mutation is undetectable in the primary due to the low sensitivity of the technique. (B) Manual backtracking of mutations in the primary tumor using deep sequencing data allowed for the identification of several hits at a very low VAF compared to the PDTX-T5. A B IL89 CTRL 30 CTRL Ruxoli?nib S 20 M Ruxoli?nib A R G 10 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 1 1 1 1 1 WEEKS AFTER ENGRAFTMENT Figure S3. -
Genomics and Functional Genomics of Malignant Pleural Mesothelioma
International Journal of Molecular Sciences Review Genomics and Functional Genomics of Malignant Pleural Mesothelioma Ece Cakiroglu 1,2 and Serif Senturk 1,2,* 1 Izmir Biomedicine and Genome Center, Izmir 35340, Turkey; [email protected] 2 Department of Genome Sciences and Molecular Biotechnology, Izmir International Biomedicine and Genome Institute, Dokuz Eylul University, Izmir 35340, Turkey * Correspondence: [email protected] Received: 22 July 2020; Accepted: 20 August 2020; Published: 1 September 2020 Abstract: Malignant pleural mesothelioma (MPM) is a rare, aggressive cancer of the mesothelial cells lining the pleural surface of the chest wall and lung. The etiology of MPM is strongly associated with prior exposure to asbestos fibers, and the median survival rate of the diagnosed patients is approximately one year. Despite the latest advancements in surgical techniques and systemic therapies, currently available treatment modalities of MPM fail to provide long-term survival. The increasing incidence of MPM highlights the need for finding effective treatments. Targeted therapies offer personalized treatments in many cancers. However, targeted therapy in MPM is not recommended by clinical guidelines mainly because of poor target definition. A better understanding of the molecular and cellular mechanisms and the predictors of poor clinical outcomes of MPM is required to identify novel targets and develop precise and effective treatments. Recent advances in the genomics and functional genomics fields have provided groundbreaking insights into the genomic and molecular profiles of MPM and enabled the functional characterization of the genetic alterations. This review provides a comprehensive overview of the relevant literature and highlights the potential of state-of-the-art genomics and functional genomics research to facilitate the development of novel diagnostics and therapeutic modalities in MPM. -
Supplementary Data
Journal of Alzheimer’s Disease 28 (2012) 1–3 1 IOS Press Supplementary Data Neuroinflammation, Hyperphosphorylated Tau, Diffuse Amyloid Plaques, and Down-Regulation of the Cellular Prion Protein in Air Pollution Exposed Children and Young Adults Lilian Calderon-Garcidue´ nas˜ a,b,∗, Michael Kavanaughb, Michelle Blockc, Amedeo D’Angiullid, Ricardo Delgado-Chavez´ e, Ricardo Torres-Jardon´ f , Angelica Gonzalez-Maciel´ a, Rafael Reynoso-Roblesa, Norma Osnayaa, Rodolfo Villarreal-Calderong, Ruixin Guoh, Zhaowei Huah, Hongtu Zhuh, George Perryi and Philippe Diazj aInstituto Nacional de Pediatr´ıa, Mexico City, Mexico bThe Center for Structural and Functional Neurosciences, The University of Montana, Missoula, MT, USA cVirginia Commonwealth University Medical Campus, Richmond, VA, USA dDepartment of Neuroscience, Carleton University, Ottawa, Ontario, Canada ePathology Department, Instituto Nacional de Cancerologia, Mexico City, Mexico f Centro de Ciencias de la Atm´osfera, Universidad Nacional Aut´onoma de Me´xico, Mexico City, Mexico gDavidson Honors College, The University of Montana, Missoula, MT, USA hDepartment of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA iCollege of Sciences, University of Texas at San Antonio, San Antonio, TX, USA jCore Laboratory for Neuromolecular Production, The University of Montana, Missoula, MT, USA Handling Editor: Massimo Tabaton Accepted 17 August 2011 ∗Correspondence to: Lilian Calderon-Garcidue´ nas,˜ MD Ph.D., The Center for Structural and Functional Neuro- sciences, The University of Montana, 32 Campus Drive, 287 Skaggs Building, Missoula, MT 59812, USA. E-mail: [email protected]. ISSN 1387-2877/12/$27.50 © 2012 – IOS Press and the authors. All rights reserved 2 L. -
Systems Pharmacology Dissection of Epimedium Targeting Tumor Microenvironment to Enhance Cytotoxic T Lymphocyte Responses in Lung Cancer
www.aging-us.com AGING 2021, Vol. 13, No. 2 Research Paper Systems pharmacology dissection of Epimedium targeting tumor microenvironment to enhance cytotoxic T lymphocyte responses in lung cancer Chao Huang1,*, Zhihua Li2,*, Jinglin Zhu2, Xuetong Chen1, Yuanyuan Hao2, Ruijie Yang2, Ruifei Huang2, Jun Zhou3, Zhenzhong Wang3, Wei Xiao3, Chunli Zheng2, Yonghua Wang1,2 1Bioinformatics Center, College of Life Sciences, Northwest A&F University, Yangling 712100, Shaanxi, China 2Key Laboratory of Resource Biology and Biotechnology in Western China, Ministry of Education, School of Life Sciences, Northwest University, Xi’an 710069, China 3State Key Laboratory of New-Tech for Chinese Medicine Pharmaceutical Process, Jiangsu Kanion Pharmaceutical, Co., Ltd., Lianyungang 222001, China *Equal contribution Correspondence to: Yonghua Wang, Chunli Zheng, Wei Xiao; email: [email protected]; [email protected], https://orcid.org/0000-0001-9552-8040; [email protected], https://orcid.org/0000-0001-8809-9137 Keywords: systems pharmacology, NSCLC, tumor microenvironment, epimedium, icaritin Received: April 15, 2020 Accepted: October 1, 2020 Published: January 17, 2021 Copyright: © 2021 Huang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT The clinical notably success of immunotherapy fosters an enthusiasm in developing drugs by enhancing antitumor immunity in the tumor microenvironment (TME). Epimedium, is a promising herbal medicine for tumor immunotherapy due to the pharmacological actions in immunological function modulation and antitumor. Here, we developed a novel systems pharmacology strategy to explore the polypharmacology mechanism of Epimedium involving in targeting TME of non-small cell lung cancer (NSCLC).