PRKAB1 Polyclonal Antibody Gene Symbol: PRKAB1

Total Page：16

File Type：pdf, Size：1020Kb

PRKAB1 polyclonal antibody Gene Symbol: PRKAB1 Gene Alias: AMPK, HAMPKb, MGC17785 Catalog Number: PAB30688 Gene Summary: The protein encoded by this gene is a Regulation Status: For research use only (RUO) regulatory subunit of the AMP-activated protein kinase Product Description: Rabbit polyclonal antibody raised (AMPK). AMPK is a heterotrimer consisting of an alpha against partial recombinant human PRKAB1. catalytic subunit, and non-catalytic beta and gamma subunits. AMPK is an important energy-sensing enzyme Immunogen: Recombinant protein corresponding to that monitors cellular energy status. In response to human PRKAB1. cellular metabolic stresses, AMPK is activated, and thus phosphorylates and inactivates acetyl-CoA carboxylase Sequence: (ACC) and beta-hydroxy beta-methylglutaryl-CoA MGNTSSERAALERHGGHKTPRRDSSGGTKDGDRPKI reductase (HMGCR), key enzymes involved in regulating LMDSPEDADLFHSEEIKAPEKEEFLAWQHDLEVNDKA de novo biosynthesis of fatty acid and cholesterol. This PAQARPTVFRWTGGGKEVYLSGSFNNW subunit may be a positive regulator of AMPK activity. The myristoylation and phosphorylation of this subunit Host: Rabbit have been shown to affect the enzyme activity and cellular localization of AMPK. This subunit may also Reactivity: Human,Mouse,Rat serve as an adaptor molecule mediating the association of the AMPK complex. [provided by RefSeq] Applications: IF, IHC-P, WB-Ce (See our web site product page for detailed applications information) Protocols: See our web site at http://www.abnova.com/support/protocols.asp or product page for detailed protocols Form: Liquid Purification: Antigen affinity purification Isotype: IgG Recommend Usage: Immunofluorescence (1-4 ug/mL) Immunohistochemistry (Formalin/PFA-fixed paraffin-embedded sections) (1:50-1:200) Western Blot (1:100-1:250) The optimal working dilution should be determined by the end user. Storage Buffer: In PBS, pH 7.2 (40% glycerol, 0.02% sodium azide). Storage Instruction: Store at 4°C. For long term storage store at -20°C. Aliquot to avoid repeated freezing and thawing. Entrez GeneID: 5564 Page 1/1 Powered by TCPDF (www.tcpdf.org).

Copy Link

Recommended publications

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.
[Show full text]
32-3099: PRKAB1 Recombinant Protein Description
9853 Pacific Heights Blvd. Suite D. San Diego, CA 92121, USA Tel: 858-263-4982 Email: [email protected] 32-3099: PRKAB1 Recombinant Protein Alternative Name : AMPK,HAMPKb,5'-AMP-activated protein kinase subunit beta-1,AMPK subunit beta-1,AMPKb,PRKAB1. Description Source : E.coli. PRKAB1 Human Recombinant produced in E.Coli is a single, non-glycosylated, polypeptide chain containing 293 amino acids (1-270 a.a.) and having a molecular mass of 32.8 kDa. The PRKAB1 is fused to a 23 amino acid His Tag at N- Terminus and purified by proprietary chromatographic techniques. 5'-AMP-activated protein kinase subunit beta-1 (PRKAB1) hinders protein, carbohydrate and lipid biosynthesis, in addition to cell growth and proliferation. AMPK is a heterotrimer comprised of an alpha catalytic subunit, and non-catalytic beta and gamma subunits. AMPK acts via direct phosphorylation of metabolic enzymes, and longer-term effects by phosphorylation of transcription regulators. PRKAB1 is a regulator of cellular polarity by remodeling the actin cytoskeleton; most likely by indirectly activating myosin. Beta non-catalytic subunit acts as a scaffold on which the AMPK complex compiles, through its C-terminus that joins alpha (PRKAA1 or PRKAA2) and gamma subunits (PRKAG1, PRKAG2 or PRKAG3). Product Info Amount : 5 µg Purification : Greater than 85% as determined by SDS-PAGE. The PRKAB1 protein solution (0.5mg/ml) contains 20mM Tris-HCl buffer (pH 8.0), 0.15M NaCl, Content : 10% glycerol and 1mM DTT. Store at 4°C if entire vial will be used within 2-4 weeks. Store, frozen at -20°C for longer periods of Storage condition : time.
[Show full text]
NFKBIZ Mutation Prevalence in the Arthur/Schmitz/Chapuy Cohorts
Supplemental Tables/Figures: Table S1: NFKBIZ mutation prevalence in the Arthur/Schmitz/Chapuy cohorts. Subtype Cohort All ABC DLC Schmitz Chapuy # patients 1006 511 330 466 210 UTR 101 (10) 66 (13) 39 (12) 49 (11) 13 (6) Amplification 86 (8.5) 66 (12.9) 23 (7) 35 (8) 28 (13) NFKBIZ Mutation TOTAL 174 (17) 120 (23.5) 57 (17) 79 (17) 38 (18) Table S2: NFKBIZ 3′ UTR mutations in other WGS cohorts. Cohort # Patients NFKBIZ UTR mutations (%) Publication BL_Adult 81 1 (1.2) Grande_et_al,2019 BL_Pediatric 124 1 (0.8) unpublished DLBCL_cell_lines 15 2 (13.3) Morin_et_al,2013 DLBCL_BC 117 11 (9.4) Arthur_et_al,2018 DLBCL_ICGC 87 11 (12.6) Hübschmann_et_al,2021 FL_ICGC 100 4 (4) Hübschmann_et_al,2021 FL_Kridel 48 1 (2.1) Kridel_et_al,2016 Table S3: COO and LymphGen classifications of DLBCLs and FLs from other cohorts. NFKBIZ UTR mutations (%) DLBCL (%) FL (%) ABC 13 (41.9) 13 (54.2) 0 (0) GCB 4 (12.9) 4 (16.7) 0 (0) COO UNCLASS 2 (6.5) 2 (8.3) 0 (0) NA 12 (38.7) 5 (20.8) 5 (100) TOTAL 31 24 5 BN2 13 (41.9) 9 (37.5) 3 (60) EZB 4 (12.9) 2 (8.3) 2 (40) ST2 1 (3.2) 1 (4.2) 0 (0) LymphGen Other 9 (29) 8 (33.3) 0 (0) Composite 2 (6.5) 2 (8.3) 0 (0) NA 2 (6.5) 2 (8.3) 0 (0) TOTAL 31 24 5 Table S4: LymphGen classifications of all patients and those with NFKBIZ mutations in Arthur/Schmitz/Chapuy cohorts.
[Show full text]
Phosphoproteomics of Retinoblastoma: a Pilot Study Identiﬁes Aberrant Kinases
molecules Article Phosphoproteomics of Retinoblastoma: A Pilot Study Identiﬁes Aberrant Kinases Lakshmi Dhevi Nagarajha Selvan 1,†, Ravikanth Danda 1,2,†, Anil K. Madugundu 3 ID , Vinuth N. Puttamallesh 3, Gajanan J. Sathe 3,4, Uma Maheswari Krishnan 2, Vikas Khetan 5, Pukhraj Rishi 5, Thottethodi Subrahmanya Keshava Prasad 3,6 ID , Akhilesh Pandey 3,7,8, Subramanian Krishnakumar 1, Harsha Gowda 3,* and Sailaja V. Elchuri 9,* 1 L&T Opthalmic Pathology, Vision Research Foundation, Sankara Nethralaya, Chennai, Tamil Nadu 600 006, India; [email protected] (L.D.N.S.); [email protected] (R.D.); [email protected] (S.K.) 2 Centre for Nanotechnology and Advanced Biomaterials, Shanmugha Arts, Science, Technology and Research Academy University, Tanjore, Tamil Nadu 613 401, India; [email protected] 3 Institute of Bioinformatics, International Technology Park, Bangalore, Karnataka 560 066, India; [email protected] (A.K.M.); [email protected] (V.N.P.); [email protected] (G.J.S.); [email protected] (T.S.K.P.); [email protected] (A.P.) 4 Manipal Academy of Higher Education (MAHE), Manipal, Karnataka 576 104, India 5 Shri Bhagwan Mahavir Vitreoretinal Services, Sankara Nethralaya, Chennai, Tamil Nadu 600 006, India; [email protected] (V.K.); [email protected] (P.R.) 6 Center for Systems Biology and Molecular Medicine, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, Karnataka 575 108, India 7 McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA 8 Departments of Biological Chemistry, Pathology and Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA 9 Department of Nanotechnology, Vision Research Foundation, Sankara Nethralaya, Chennai, Tamil Nadu 600 006, India * Correspondence: [email protected] (H.G.); [email protected] (S.V.E.); Tel.: +91-80-28416140 (H.G.); +91-44-28271616 (S.V.E.) † These authors contributed equally to this work.
[Show full text]
Original Article a Database and Functional Annotation of NF-Κb Target Genes
Int J Clin Exp Med 2016;9(5):7986-7995 www.ijcem.com /ISSN:1940-5901/IJCEM0019172 Original Article A database and functional annotation of NF-κB target genes Yang Yang, Jian Wu, Jinke Wang The State Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096, People’s Republic of China Received November 4, 2015; Accepted February 10, 2016; Epub May 15, 2016; Published May 30, 2016 Abstract: Backgrounds: The previous studies show that the transcription factor NF-κB always be induced by many inducers, and can regulate the expressions of many genes. The aim of the present study is to explore the database and functional annotation of NF-κB target genes. Methods: In this study, we manually collected the most complete listing of all NF-κB target genes identified to date, including the NF-κB microRNA target genes and built the database of NF-κB target genes with the detailed information of each target gene and annotated it by DAVID tools. Results: The NF-κB target genes database was established (http://tfdb.seu.edu.cn/nfkb/). The collected data confirmed that NF-κB maintains multitudinous biological functions and possesses the considerable complexity and diversity in regulation the expression of corresponding target genes set. The data showed that the NF-κB was a central regula- tor of the stress response, immune response and cellular metabolic processes. NF-κB involved in bone disease, immunological disease and cardiovascular disease, various cancers and nervous disease. NF-κB can modulate the expression activity of other transcriptional factors. Inhibition of IKK and IκBα phosphorylation, the decrease of nuclear translocation of p65 and the reduction of intracellular glutathione level determined the up-regulation or down-regulation of expression of NF-κB target genes.
[Show full text]
Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients with Stable Coronary Heart Disease
Supplementary Online Content Ganz P, Heidecker B, Hveem K, et al. Development and validation of a protein-based risk score for cardiovascular outcomes among patients with stable coronary heart disease. JAMA. doi: 10.1001/jama.2016.5951 eTable 1. List of 1130 Proteins Measured by Somalogic’s Modified Aptamer-Based Proteomic Assay eTable 2. Coefficients for Weibull Recalibration Model Applied to 9-Protein Model eFigure 1. Median Protein Levels in Derivation and Validation Cohort eTable 3. Coefficients for the Recalibration Model Applied to Refit Framingham eFigure 2. Calibration Plots for the Refit Framingham Model eTable 4. List of 200 Proteins Associated With the Risk of MI, Stroke, Heart Failure, and Death eFigure 3. Hazard Ratios of Lasso Selected Proteins for Primary End Point of MI, Stroke, Heart Failure, and Death eFigure 4. 9-Protein Prognostic Model Hazard Ratios Adjusted for Framingham Variables eFigure 5. 9-Protein Risk Scores by Event Type This supplementary material has been provided by the authors to give readers additional information about their work. Downloaded From: https://jamanetwork.com/ on 10/02/2021 Supplemental Material Table of Contents 1 Study Design and Data Processing ......................................................................................................... 3 2 Table of 1130 Proteins Measured .......................................................................................................... 4 3 Variable Selection and Statistical Modeling ........................................................................................
[Show full text]
Cells Phenotype of Human Tolerogenic Dendritic Glycolytic
High Mitochondrial Respiration and Glycolytic Capacity Represent a Metabolic Phenotype of Human Tolerogenic Dendritic Cells This information is current as of September 26, 2021. Frano Malinarich, Kaibo Duan, Raudhah Abdull Hamid, Au Bijin, Wu Xue Lin, Michael Poidinger, Anna-Marie Fairhurst and John E. Connolly J Immunol published online 27 April 2015 http://www.jimmunol.org/content/early/2015/04/25/jimmun Downloaded from ol.1303316 Supplementary http://www.jimmunol.org/content/suppl/2015/04/25/jimmunol.130331 http://www.jimmunol.org/ Material 6.DCSupplemental Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists by guest on September 26, 2021 • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2015 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published April 27, 2015, doi:10.4049/jimmunol.1303316 The Journal of Immunology High Mitochondrial Respiration and Glycolytic Capacity Represent a Metabolic Phenotype of Human Tolerogenic Dendritic Cells Frano Malinarich,*,† Kaibo Duan,† Raudhah Abdull Hamid,*,† Au Bijin,*,† Wu Xue Lin,*,† Michael Poidinger,† Anna-Marie Fairhurst,† and John E.
[Show full text]
AMPK Causes Cell Cycle Arrest in LKB1-Deficient Cells Via Activation of CAMKK2
Published OnlineFirst May 2, 2016; DOI: 10.1158/1541-7786.MCR-15-0479 Cell Cycle and Senescence Molecular Cancer Research AMPK Causes Cell Cycle Arrest in LKB1-Deficient Cells via Activation of CAMKK2 Sarah Fogarty, Fiona A. Ross, Diana Vara Ciruelos, Alexander Gray, Graeme J. Gowans, and D. Grahame Hardie Abstract The AMP-activated protein kinase (AMPK) is activated by also caused G1 arrest similar to that caused by expression of LKB1, phosphorylation at Thr172, either by the tumor suppressor kinase while expression of a dominant-negative AMPK mutant, or a þ LKB1 or by an alternate pathway involving the Ca2 /calmodulin- double knockout of both AMPK-a subunits, also prevented the dependent kinase, CAMKK2. Increases in AMP:ATP and ADP:ATP cell-cycle arrest caused by A23187. These mechanistic findings ratios, signifying energy deficit, promote allosteric activation and confirm that AMPK activation triggers cell-cycle arrest, and also net Thr172 phosphorylation mediated by LKB1, so that the LKB1– suggest that the rapid proliferation of LKB1-null tumor cells is due AMPK pathway acts as an energy sensor. Many tumor cells carry to lack of the restraining influence of AMPK. However, cell-cycle loss-of-function mutations in the STK11 gene encoding LKB1, but arrest can be restored by reexpressing LKB1 or a constitutively LKB1 reexpression in these cells causes cell-cycle arrest. Therefore, active CAMKK2, or by pharmacologic agents that increase intra- þ it was investigated as to whether arrest by LKB1 is caused by cellular Ca2 and thus activate endogenous CAMKK2. activation of AMPK or of one of the AMPK-related kinases, which are also dependent on LKB1 but are not activated by CAMKK2.
[Show full text]
The Role of MDM2 and CDK4 in Well Differentiated Liposarcoma Dr
The role of MDM2 and CDK4 in well differentiated liposarcoma Dr Rachel Katherine Conyers Submitted in total fulfillment of the requirements of the degree of Doctor of Philosophy April 2015 Department of Pathology The University of Melbourne i Abstract Transformation of normal cells to cancer cells is tightly linked to fundamental changes in cell cycle regulation. In addition, oncogenes can aberrantly enhance cell proliferation. Two genes; Cyclin dependent kinase-4 (CDK4) and Murine double minute 2 (MDM2) are amplified and overexpressed in over 90% of well differentiated liposarcomas. Their role in cell cycle control, and regulation of tumour suppressor p53 respectively, strongly suggesting that deregulation of these genes confers some selective advantage to this tumour. To elucidate the role of these genes in the development and progression of liposarcoma I have used transgenic mouse models and in vitro assays. Given the recent development of novel CDK4 inhibitors, I have tested several CDK4 inhibitors (sc-203873, sc-203874, NPCD, PD 0332991) on liposarcoma cell lines (449B, T1000, 778, GOT3) to determine sensitivity to inhibition, cell cycle arrest and downstream effects of inhibition. PD033991 was found to be the most selective and sensitive CDK4 inhibitor and, as such, was used in a siRNA screen of the genome to identify co-modifiers of CDK4 inhibition. A total of 13 genes were identified that produced a resistance phenotype in the context of CDK4 inhibition. Two of these genes; Arrestin, beta 2 (ARRB2) and Dysferlin (DYSF) demonstrated a reproducible resistance phenotype in a series of functional validation studies. ii Declaration This is to certify that: i the thesis comprises only my original work towards the PhD except where indicated in the Preface, ii due acknowledgement has been made in the text to all other material used, iii the thesis is fewer than 100 000 words in length, exclusive of tables, maps, bibliographies and appendices.
[Show full text]
Human Kinases Info Page
Human Kinase Open Reading Frame Collecon Description: The Center for Cancer Systems Biology (Dana Farber Cancer Institute)- Broad Institute of Harvard and MIT Human Kinase ORF collection from Addgene consists of 559 distinct human kinases and kinase-related protein ORFs in pDONR-223 Gateway® Entry vectors. All clones are clonal isolates and have been end-read sequenced to confirm identity. Kinase ORFs were assembled from a number of sources; 56% were isolated as single cloned isolates from the ORFeome 5.1 collection (horfdb.dfci.harvard.edu); 31% were cloned from normal human tissue RNA (Ambion) by reverse transcription and subsequent PCR amplification adding Gateway® sequences; 11% were cloned into Entry vectors from templates provided by the Harvard Institute of Proteomics (HIP); 2% additional kinases were cloned into Entry vectors from templates obtained from collaborating laboratories. All ORFs are open (stop codons removed) except for 5 (MST1R, PTK7, JAK3, AXL, TIE1) which are closed (have stop codons). Detailed information can be found at: www.addgene.org/human_kinases Handling and Storage: Store glycerol stocks at -80oC and minimize freeze-thaw cycles. To access a plasmid, keep the plate on dry ice to prevent thawing. Using a sterile pipette tip, puncture the seal above an individual well and spread a portion of the glycerol stock onto an agar plate. To patch the hole, use sterile tape or a portion of a fresh aluminum seal. Note: These plasmid constructs are being distributed to non-profit institutions for the purpose of basic
[Show full text]
PRKAB1 (Human) Cell-Based ELISA Cellular Localization of AMPK
PRKAB1 (Human) Cell-Based ELISA cellular localization of AMPK. This subunit may also Kit serve as an adaptor molecule mediating the association of the AMPK complex. [provided by RefSeq] Catalog Number: KA2571 Regulatory Status: For research use only (RUO) Product Description: PRKAB1 (Human) Cell-Based ELISA Kit is an indirect enzyme-linked immunoassay for qualitative determination of PRKAB1 expression in cultured cells. Suitable Sample: Attached Cell Label: HRP-conjugated Detection Method: Colorimetric Reactivity: Human,Mouse,Rat Applications: Qual (See our web site product page for detailed applications information) Protocols: See our web site at http://www.abnova.com/support/protocols.asp or product page for detailed protocols Storage Instruction: Store the kit at 4°C. Entrez GeneID: 5564 Gene Symbol: PRKAB1 Gene Alias: AMPK, HAMPKb, MGC17785 Gene Summary: The protein encoded by this gene is a regulatory subunit of the AMP-activated protein kinase (AMPK). AMPK is a heterotrimer consisting of an alpha catalytic subunit, and non-catalytic beta and gamma subunits. AMPK is an important energy-sensing enzyme that monitors cellular energy status. In response to cellular metabolic stresses, AMPK is activated, and thus phosphorylates and inactivates acetyl-CoA carboxylase (ACC) and beta-hydroxy beta-methylglutaryl-CoA reductase (HMGCR), key enzymes involved in regulating de novo biosynthesis of fatty acid and cholesterol. This subunit may be a positive regulator of AMPK activity. The myristoylation and phosphorylation of this subunit have been shown to affect the enzyme activity and Page 1/1 Powered by TCPDF (www.tcpdf.org).
[Show full text]
Identification of Kinase Inhibitor Targets in the Lung Cancer Microenvironment by Chemical and Phosphoproteomics
Published OnlineFirst September 4, 2014; DOI: 10.1158/1535-7163.MCT-14-0152 Molecular Cancer Models and Technologies Therapeutics Identification of Kinase Inhibitor Targets in the Lung Cancer Microenvironment by Chemical and Phosphoproteomics Manuela Gridling1, Scott B. Ficarro2,3,4, Florian P. Breitwieser1, Lanxi Song5, Katja Parapatics1, Jacques Colinge1, Eric B. Haura5, Jarrod A. Marto2,3,4, Giulio Superti-Furga1, Keiryn L. Bennett1, and Uwe Rix1,6 Abstract A growing number of gene mutations, which are recognized as cancer drivers, can be successfully targeted with drugs. The redundant and dynamic nature of oncogenic signaling networks and complex interactions between cancer cells and the microenvironment, however, can cause drug resistance. While these challenges can be addressed by developing drug combinations or polypharmacology drugs, this benefits greatly from a detailed understanding of the proteome-wide target profiles. Using mass spectrometry-based chemical proteomics, we report the comprehensive characterization of the drug–protein interaction networks for the multikinase inhibitors dasatinib and sunitinib in primary lung cancer tissue specimens derived from patients. We observed in excess of 100 protein kinase targets plus various protein complexes involving, for instance, AMPK, TBK1 (sunitinib), and ILK (dasatinib). Importantly, comparison with lung cancer cell lines and mouse xenografts thereof showed that most targets were shared between cell lines and tissues. Several targets, however, were only present in tumor tissues. In xenografts, most of these proteins were of mouse origin suggesting that they originate from the tumor microenvironment. Furthermore, intersection with subsequent global phosphoproteomic analysis identified several activated signaling pathways. These included MAPK, immune, and integrin signaling, which were affected by these drugs in both cancer cells and the microen- vironment.
[Show full text]