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Myelodysplastic Syndromes SUPPLEMENTARY APPENDIX Transforming growth factor 1- mediated functional inhibition of mesenchymal stromal celβls in myelodysplastic syndromes and acute myeloid leukemia Stefanie Geyh, 1* Manuel Rodríguez-Paredes, 1,2 * Paul Jäger, 1 Annemarie Koch, 1 Felix Bormann, 2 Julian Gutekunst, 2 Christoph Zilkens, 3 Ulrich Germing, 1 Guido Kobbe, 1 Frank Lyko, 2 Rainer Haas 1 and Thomas Schroeder 1 1Department of Hematology, Oncology and Clinical Immunology, University of Duesseldorf, Medical Faculty; 2Division of Epigenetics, DKFZ- ZMBH Alliance, German Cancer Research Center, Heidelberg and 3Department of Orthopedic Surgery, University of Duesseldorf, Medical Faculty, Germany *SG and MR-P contributed equally to this work. ©2018 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2017.186734 Received: December 19, 2017. Accepted: May 14, 2018. Pre-published: May 17, 2018. Correspondence: [email protected] Figure S1 Downregulated genes Downregulated genes Upregulated Figure S1. Heatmaps showing the 50 most upregulated and downregulated genes between the 3 healthy MSC controls and the 9 RCMD-, RAEB- and AML-derived MSC samples. Color scale depicts the rlog-transformed FPKM values for each gene and every sample. Figure S2 Downregulated genes Downregulated genes Upregulated Figure S2. Heatmaps showing the 50 most upregulated and downregulated genes between the 3 healthy MSC controls and the 3 RCMD, RAEB and AML MSC samples, respectively. Color scales depict the rlog-transformed FPKM values for each gene and every sample. Figure S3 A. B. 0.0015 *** ** <-3 -2 0.0010 RCMD RAEB AML -1 0 1 0.0005 Log2FC LTF 2 CCL26/GAPDH INHBB >3 0.0000 TGFB2 y S h D ML M A ealt ll LTF H a EGF 0.003 *** ** INHBB TGFB2 0.002 INHBB IGFBP7 0.001 GDF11 LIF/GAPDH BMP1 0.000 y L th M TNFSF12 l A FGF13 ea ll MDS H a FGF13 0.0015 * TNFSF10 TNFSF10 0.0010 0.0005 SPP1/GAPDH 0.0000 y th l AML ea H all MDS Figure S3. A. Heatmap depicting the expression changes of the specific set of cytokines found statistically significantly ( q<0.05) deregulated in the MSC from RCMD, RAEB and AML patients. FC: expression fold change. B. To validate the results obtained by RNA seq gene expression of 3 candidate cytokines was analyzed by qPCR in an independent set of patient-derived MSC (MDS n=32; AML n=10) in comparison to MSC of healthy controls (n=25). As shown in the figure, the results from this analysis confirmed the results obtained by RNA seq. Asterisks display p-values * p<0.5, ** p<0.01, *** p<0.001. Figure S4 Figure S4. Ingenuity Pathway Analyses (IPA) of the specific sets of genes found deregulated in each one of the three myeloid subentities. Only the first five predicted secreted upstream regulators are shown for each malignancy. In the case of RAEB, TGF !1 appears in the 7th position with a statistically significant p-value of 1.19E-04. Figure S5 Medium + Supplements Growth Differentiation Cultivation Gene expression Healthy MSC Hematopoietic support Figure S5. Schematic of the cell culture experiments. Healthy were cultured in the presence of TGFß1 and/or TGFßR1 kinase inhibitor SD-208. After this pre-incubation MSC were then analysed with regard to their growth and differentiation potential as well as gene expression and hematopoietic support capacities. The concentrations of TGFß1 and SD-208 are given in the Methods section and are accordance with previous reports (21-23). Figure S6 ** 5.0 ×10 6 ** 4.0 ×10 6 *** 3.0 ×10 6 2.0 ×10 6 6 MSC cell number cell MSC 1.0 ×10 0 F S G y Ctrl +T MD AML /SD208 th F eal G H +T Figure S6. Bar charts show the absolute MSC numbers after 3 days pre-incubation of 2x10 5 healthy MSC with TGFß1 (10 ng/ml) in comparison to untreated primary MDS- and AML-derived MSC. Asteriks display p-values, ** p<0.01, *** p<0.001. Figure S7 U U UL U R:7 Figure S7. Healthy MSC were treated for the respective factors for 14 days. Afterwards osteogenic differentiation was visualized by Alizarin Red staining. Representative micrographs with scale bars indicating 100 µm. Figure S8 20 0 -20 PC2 (31% variance) (31% PC2 Control TGF !1 -40 TGF !1+SD208 -30 0 30 PC1 (46% variance) Figure S8. Principal component analysis performed with RNA-seq data from healthy MSC treated for 28 days with DMSO (control), TGF !1 or TGF !1 with SD-208. Gene expression data clearly separates the samples along PC1 (the treatments) and PC2 (the two biological replicates). Figure S9 TGF !1-treated healthy MSC (donor 1) *** *** *** *** *** *** Arbitrary units Arbitrary TGF !1-treated healthy MSC (donor 2) *** *** *** *** *** ** Arbitrary units Arbitrary Figure S9. Healthy MSC (n=2 donors) were pre-incubated with TGF !1 and/or SD-208 for up to 28 days. Medium was changed every 3 days supplemented with DMSO, TGF !1 or TGF !1 with SD-208 at a concentration ranging from 5ng/ml to 10ng/ml. Subsequently, qRT-PCR experiments were performed to assess the expression of TBX15 , PITX2 and HOXB6 . Statistical significance was determined with the Student’s t-test (** p<0.01, *** p<0.001). Figure S10 5 ** * * 4 *** 3 2 MFI of Jagged1 of MFI 1 0 O 8 HC GF SD20 +T +DMS + +TGF/SD208 Figure S10. To test a potential of SD-208 alone to induce the expression of Jagged1, healthy MSC were incubated with SD-208 (n=3). Bar charts illustrate that SD-208 did not influence the protein expression of Jagged1 after 7 days as measured by flow cytometry. Asterisks display p-values * p<0.05, ** p<0.01. Figure S11 0.0006 0.0005 0.003 0.07 * 0.06 0.0004 0.0004 0.002 0.0003 0.0002 0.0002 0.001 LIF/GAPDH CCL26/GAPDH SPP1/GAPDH 0.0001 0.0000 0.0000 0.000 C C F C F H GF H G H TG +T +T + Figure S11. To test whether TGF !1 influences the expression of 3 candidate cytokines in the same direction as detected in the primary patient-derived MSC we measured their gene expression using quantitative PCR prior (n=6) and after 14d of treatment with TGF !1 (n=6). As shown in the figure, the results from this analysis confirmed the results obtained by RNA seq. Asterisks display p-values * p<0.05. Figure S12 0.3 0.2 0.1 0.078 Figure S12. LTC-IC frequency [%] either native or pre-incubated with SD-208. 0.0 Bar charts show LTC-IC frequencies of healthy CD34+ HSPC MDS/AML +DMSO +SD2 08 cultured on MDS- and AML-derived MSC (n=6) Figure S13 0.08 * * 0.06 0.04 0.02 TGFß-1/GAPDH 0.00 S L D M A + 4+ M D3 D34 C C CD34+ Healthy Figure S13. RNA expression of TGF !1 was analyzed in CD34+ HSPC cells from patients with MDS (n=7) and AML (n=13) in comparison to healthy controls (n=20). Sequences of the primers can be provided on request. Figure S14 14 12 10 8 Expression (RSEM) Expression 6 4 Figure S14. Box plot showing TGF !1 expression (RNAseq) in 28 different healthy tissues (967 samples), 36 different tumor entities (12,974 samples) and 173 AML samples from TCGA database. Highest p-value between comparisons ( t-test): 6,179E-31. Table S1. Patients Demographics. MDS Patient Age Gender WHO 2008/2016 IPSS IPSS-R Karyotype MDS1 61 female RARS/MDS-RS-SLD low low Normal MDS2 60 male RCMD/MDS-MLD low low Normal MDS3 58 male RCMD/MDS-MLD intermediate-1 low Normal MDS4 89 male RCMD/MDS-MLD Intermediate-1 intermediate Trisomy 8 MDS5 65 male RCMD-RS/MDS-RS-MLD low low Normal 46,XY MDS6 47 male RCMD/MDS-MLD intermediate-2 intermediate +1.der(1;7)(q10;p10)[13];46,XY[7] MDS7 64 male RAEB I/MDS-EB-I intermediate-2 high Complex MDS8 74 male RAEB II/MDS-EB-II intermediate-1 intermediate Normal MDS9 72 male RAEB II//MDS-EB-II intermediate-2 high 5q-, t(11;12) MDS10 80 male RAEB II/MDS-EB-II Missing missing Missing MDS11 57 male RAEB I/MDS-EB-I intermediate-2 high 46,XY[27], FISH: -7, +17 MDS12 46 male RCMD/MDS-MLD low low 46,XY[22] MDS13 39 male RAEB II/MDS-EB-II intermediate-1 intermediate +8, XXY, add(21p) AML Genetic Patient Age Gender WHO 2008/2016 FAB Karyotype Aberrations AML with myelodysplasia related AML1 49 male M4 no mutations Normal changes AML with myelodysplasia related AML2 54 male M1 no mutations Complex changes AML3 67 male AML therapy-related M4 not tested 46 XY, t(14;16)[21]/ 46 XY [6] AML4 34 female AML NOS M0/1 FLT3-ITD Normal 46, XY, AML5 67 male AML NOS M5 FLT3-ITD del(20)(q11.2q13.1)(17)/47,idem, +21(4) AML6 48 male AML with recurrent genetic changes M4 FLT3-ITD , NPM-1 Normal AML with myelodysplasia related AML7 55 male M0 no mutations Complex changes AML with myelodysplasia related AML8 71 male M5b no mutations Complex changes AML9 49 male AML NOS M4 not tested not tested AML10 25 male AML with recurrent genetic changes M2/4 FLT3-ITD t(6;9) AML with myelodysplasia related 46,XY, +1, AML11 60 male M1 no mutations changes der(1;7)(q10;q10)[3]/46,XY[27] AML with myelodysplasia related AML12 55 male M1 RUNX1 46,XY[24] changes AML with myelodysplasia related AML13 62 female M2 no mutations complex changes AML with myelodysplasia related IDH2-Mutation, no AML14 62 female M1 t(3;21) changes other mutations FLT3-TKD , NPM-1, AML15 57 male AML with recurrent genetic changes M1 SF3B1+, NRAS+, 46,XY [22] TET2+ Table S1.
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  • Genomic Aberrations Associated with Erlotinib Resistance in Non-Small Cell Lung Cancer Cells

    Genomic Aberrations Associated with Erlotinib Resistance in Non-Small Cell Lung Cancer Cells

    ANTICANCER RESEARCH 33: 5223-5234 (2013) Genomic Aberrations Associated with Erlotinib Resistance in Non-small Cell Lung Cancer Cells MASAKUNI SERIZAWA1, TOSHIAKI TAKAHASHI2, NOBUYUKI YAMAMOTO2,3 and YASUHIRO KOH1 1Drug Discovery and Development Division, Shizuoka Cancer Center Research Institute, Sunto-gun, Shizuoka, Japan; 2Division of Thoracic Oncology, Shizuoka Cancer Center Hospital, Sunto-gun, Shizuoka, Japan; 3Third Department of Internal Medicine, Wakayama Medical University, Kimiidera, Wakayama, Japan Abstract. Background/Aim: Mechanisms of resistance to mutations develop resistance, usually within one year of epidermal growth factor receptor (EGFR)-tyrosine kinase treatment. Therefore, there is an urgent need to elucidate the inhibitors (TKIs) in non-small cell lung cancer (NSCLC) underlying mechanisms of resistance in such tumors to are not fully-understood. In this study we aimed to overcome this obstacle (11-14, 17, 24). Recent studies elucidate remaining unknown mechanisms using erlotinib- suggest that mechanisms of acquired resistance to EGFR- resistant NSCLC cells. Materials and Methods: We TKIs can be categorized into three groups: occurrence of performed array comparative genomic hybridization genetic alterations, activation of downstream pathways via (aCGH) to identify genomic aberrations associated with bypass signaling, and phenotypic transformation (15, 16, 21); EGFR-TKI resistance in erlotinib-resistant PC-9ER cells. therapeutic strategies to overcome these resistance Real-time polymerase chain reaction (PCR) and mechanisms are under development. However, although the immunoblot analyses were performed to confirm the results causes of acquired resistance to EGFR-TKIs have been of aCGH. Results: Among the five regions with copy investigated, in more than 30% of patients with acquired number gain detected in PC-9ER cells, we focused on resistance to EGFR-TKI treatment, the mechanisms remain 22q11.2-q12.1 including v-crk avian sarcoma virus CT10 unknown (15).