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A C CD3+/CD8+/CD103+T cells TIL PBMC BCL-2 CD127 KLRG1 250 100 100 83% 51% 98% 27% 1% 200 (3069) (4944) 80 (7814) (10001) 80 150 CD3 100 60 60 50 40 Patient 81 40 Patient 83 0 20 20 250 53% 200 40% 0 0 (20897) (16848) 150 CD4 100 number 100 number 70% 6% 1% 100 80 (4724) (8426) 80 50 Cell Cell 0 60 60 250 Patient 82 Patient 84 36% 15% 40 40 200 (16560) (7304) CD8 20 150 20 100 0 0 50 102 103 104 105 102 103 104 105 102 103 104 105 0 102 103 104 105 102 103 104 105 Fluorescence intensity Fluorescence intensity Fluorescence D intensity Size selected cells 100 MHC-I Epcam E-cadherin PD-L1 TIL 250 cells 90% 91% 74% 57% 80 200 PBMC (19848) (11441) (3048) (7513) 150 60 100 Patient 103 50 selected 40 0 number 250 89% 80% 52% 76% 20 200 (32218) (35051) (4870) (10298) among Cell 150 Patient 104 % 0 100 CD3 CD4 CD8 50 0 102 103 104 105 102 103 104 105 102 103 104 105 102 103 104 105 B Fluorescence intensity Volcanoplot TIL versus PBMC 100 cells 30 80 ) 25 60 selected 20 40 p-value 15 size- 20 10 0 5 among Log10(Adj. % 0 MHC-I Epcam PD-L1 -5 0 5 E-cadherin Log2(FC) FC > 2 Underexpressed: 233 P-value ≤ 10-10 Overexpressed : 254 Supplemental Figure 1 A. Expression of CD3, CD4 and CD8 T-cell markers on TIL isolated from a NSCLC tumor on the basis of small cell size selection and NSCLC patient PBMC. Upper panel: TIL and PBMC were analyzed by flow cytometry using anti-CD3, anti-CD4 or anti-CD8 mAb (black fill) or an isotypic control (gray fill). Lower panel: Mean percentages of CD3+, CD4+ and CD8+ T cells among size-selected TIL (n=13) and PBMC (n=19). B. Global gene expression analyses of patient TIL and PBMC. Differential analysis of gene expression profiles in NSCLC patient TIL (n=13) and PBMC (n=19) are shown. Genes of interest were selected using a FC > 2 and a p-value ≤ 10-10 (487 genes). A subset of 103 genes with intensity higher than 1,000 in TIL samples was selected for further analysis. C. Expression of Bcl-2, CD127 and KLRG1 in CD3+/CD8+/CD103+ freshly size-selected NSCLC TIL. Flow cytometry analysis of intracytoplasmic (Bcl-2) and surface (CD127 and KLRG1) protein expression was performed using specific Ab (black fill) or corresponding isotypic controls (gray fill). Two representative experiments are included. D. Expression of MHC-I, Epcam, E-cadherin and PDL-1 on cell-sorted tumor cells. Percentages of positive cells are indicated; mean fluorescence intensities are in parentheses. Lower panel: Mean percentages of MHC-I+, Epcam+, E-cadherin+ and PD-L1+ cells among large size-selected cells (n=8). A Z-score B -2,5 2,7 TIL PBMC PBMC TIL 400 200 Fc 300 Fc 150 RGS1 200 RALGDS 100 ITGAE 50 100 ITM2B ITGB2 6 PLEK RGS-1 10 ARRB2 4 PXN 5 2 APLP2 TNFRSF-4 0 VCL 0 Adhesion PTGER2 400 ITGAM 60 CD33 300 C5AR1 Fc 40 Fc 200 CD36 CSF3R 100 VCAN 20 S100A9 12 GP1BB 6 ICOS 9 PPBP 4 RALGDS PF4 Activation 6 TNFRSF9 2 3 TNFRSF4 ICOS 0 0 IL15 100 Activation IL17RA Adhesion Fc PDCD1 600 80 LAG3 300 CTLA4 60 TNFRSF18 Fc 40 HAVCR2 Exhaustion IL6 60 20 IL21 6 Inhibition HSPA1B 40 TNFRSF-9 HSPA1A ITGAE 4 CYR61 20 HSPD1 2 GADD45G 0 BAG3 0 TNFSF9 CCR5 RASD1 BIRC3 320 JUN EGR1 150 240 BIK Fc 100 Fc 160 Apoptosis TNFAIP3 50 NR4A2 80 TFRC 30 EGR2 25 12 SERPINB9 20 9 BAG-3 IFIH1 PDCD1 15 ST6GAL1 10 6 BNIP2 5 3 TSPO CDKN2D 0 AIF1 LYN 40 NLRP3 FGR 80 LST1 Fc LILRB2 60 30 CFP 20 Fc 40 S100A8 S100A9 20 15 FCN1 S100A12 6 EGR-1 10 Inflammation PPBP 4 LAG-3 5 MAP3K3 Apoptosis KLF13 2 TKT 0 0 KCNQ1 ZNF385A LMO2 100 ASGR2 80 KLF13 400 Metal Ion SMARCD3 Fc 60 200 SPI1 Fc 40 binding MAFB 20 MTPN 20 ARRB2 15 PTGER2 6 NR4A2 SLC7A7 Exhaustion 10 Regulation ACRBP 4 CHP1 CTLA-4 5 2 DNA SH3BGRL PTP4A2 0 0 VAMP3 Proliferation HSD17B11 LAMTOR1 P34 P35 P36 P37 P38 P39 P40 P41 DENND5A FBXL5 200 100 PTPLAD2 Fc C10ORF54 25 SLC16A5 THEMIS2 20 FAM101B 15 AP1S2 C NACC2 10 AHNAK KBTBD11 5 MPEG1 250 Other TNFRSF-18 R² = 0.811 CPVL 0 functions LRRC25 200 PRAM1 PLBD1 20 Fc RGS18 150 NRGN Fc 15 10 100 Chip 6 4 50 HAVCR-2 2 0 0 100 200 300 P34 P35 P36 P37 P38 P39 P40 P41 qRT-PCR Fc P 34 P 35 P 36 P 37 P 38 P 39 P 40 P 41 P 42 P 43 P 44 P 45 P 46 P 47 P 48 P 49 P 50 P 51 P 52 P 53 P 54 P 55 P 56 P 57 P 58 P 59 P 60 P 61 P 62 P 63 P 64 P 65 Supplemental Figure 2 A. Heat map of gene expression of the 103-gene subset. Data were bi-clusterized by genes and by samples using Pearson’s coefficient as the distance metric and the Ward method for clusterization. The magnitude of relative expression of a particular gene is shown in color (LogRatio). Microarray analysis was performed using Ingenuity Pathway Analysis (IPA) and DAVID Bioinformatics. B. qRT-PCR analyses of selected genes. qRT-PCR validation of genes differentially expressed in TIL and patient PBMC. The expression of genes differentially expressed in TIL from 8 NSCLC tumors (4 SCC, 1 LCC and 3 ADC) and PBMC from 8 NSCLC patients (3 SCC, 1 LCC and 4 ADC). C. Correlation between microarray analysis and qRT-PCR in TIL and PBMC. Supplemental Table I: Complete results of the univariate and the multivariates analyses for the overall survival outcome a b c Univariate Multivariate Multivariate Multivariate HR 95% CI P-v HR 95% CI P-v HR 95% CI P-v HR 95% CI P-v CD3 Total 0.97 (0.91-1.04) 0.40 CD3 Tumor 0.94 (0.76-1.15) 0.50 CD3 Stroma 0.97 (0.89-1.06) 0.50 CD8 Total 0.90 (0.8-1.02) 0.10 CD8 Tumor 0.83 (0.63-1.09) 0.20 CD8 Stroma 0.88 (0.74-1.05) 0.20 CD103 Total 0.88 (0.77-0.99) 0.04 0.89 (0.78-1.02) 0.09 CD103 Tumor 0.84 (0.69-1.03) 0.09 0.84 (0.66-1.05) 0.13 CD103 Stroma 0.78 (0.62-0.98) 0.03 0.84 (0.67-1.06) 0.14 for an increase of 50 units Age <65 1.00 1.00 1.00 1.00 ≥65 2.99 (1.62-5.51) 0.001 2.17 (1.11-4.21) 0.02 2.15 (1.1-4.22) 0.03 2.36 (1.23-4.53) 0.01 Gender Female 1.00 1.00 1 1.00 Male 1.70 (0.86-3.37) 0.10 1.85 (0.85-4.01) 0.12 1.89 (0.87-4.12) 0.11 1.79 (0.83-3.89) 0.14 Smoking status Ever 1.00 Never 0.52 (0.16-1.69) 0.30 Stage Stade Ia 1.00 1.00 1 1.00 Stade Ib 1.67 (0.84-3.32) 0.10 1.57 (0.72-3.44) 0.26 1.54 (0.7-3.36) 0.28 1.50 (0.69-3.26) 0.31 Histology ADC 1.00 1.00 1 1.00 SCC 2.58 (1.35-4.92) 0.004 1.62 (0.76-3.45) 0.21 1.75 (0.82-3.75) 0.15 1.52 (0.71-3.25) 0.28 Others 1.15 (0.38-3.47) 0.80 1.26 (0.42-3.77) 0.68 1.31 (0.43-4) 0.64 1.10 (0.37-3.23) 0.87 Stage Ia: pT1N0 and stage Ib: pT2N0. HR: hazard ratio, CI: confidence interval. The HR (95% CI) were calculated for an increment of 50 for CD3, CD8 and CD103. P-v: Wald test p-values. a-c: three multivariate cox regression models adjusted on the clinical factors (age, gender, smoking stauts, stage and histology), and including CD103 Total (a), CD103 Tumor (b) and CD103 Stroma (c). Supplemental Table II: Differential gene expression profiles of NSCLC TIL and patient PBMC Genes more strongly expressed in TIL than in PBMC Sequence name Accession N° Sequence description FC Int TIL Int PBMC Adhesion RGS1 NM_002922 Regulator of G-protein signaling 1 24 40364 1700 RALGDS NM_001042368 Ral guanine nucleotide dissociation stimulator 2 2472 1293 ITGAE NM_002208 Integrin, alpha E (Ag CD103) 2 1132 312 Exhaustion PDCD1 NM_005018 Programmed cell death 1 13 7880 620 LAG3 NM_002286 Lymphocyte activation gene 3 10 9284 890 CTLA4 NM_005214 Cytotoxic T-lymphocyte-associated protein 4 9 3786 428 TNFRSF18 NM_148901 Tumor necrosis factor receptor superfamily, member 18 8 1465 180 HAVCR2 NM_032782 Hepatitis A virus cellular receptor 2 2 2974 1690 Immunosupression IL-6 NM_000600 Interleukin 6 (interferon, beta 2) 11 1976 178 IL-21 NM_021803 Interleukin 21 (IL21), transcript variant 1 8 109855 9136 Activation TNFRSF9 NM_001561 Tumor necrosis factor receptor superfamily, member 9 17 1198 70 TNFSF4 NM_003327 Tumor necrosis factor receptor superfamily, member 4 13 7100 546 ICOS NM_012092 Inducible T-cell co-stimulator 8 10073 1306 Apoptosis HSPA1B NM_005346 Heat shock 70kDa protein 1B 233 75665 325 HSPA1A NM_005345 Heat shock 70kDa protein 1A 110 156625 1416 CYR61 NM_001554 Cysteine-rich, angiogenic inducer, 61 27 19617 4852 HSPB1 NM_002156 Heat shock 60kDa protein 1 (chaperonin) 12 5256 1822 GADD45G NM_006705 Growth arrest and DNA-damage-inducible, gamma 10 3282 309 BAG-3 NM_004281 BCL2-associated athanogene 3 10 5256 1822 TNFSF9 NM_003811 Tumor necrosis factor (ligand) superfamily, member 9 8 1632 199 CCR5 NM_000579 Chemokine (C-C motif) receptor 5 8 7020 910 RASD1 NM_016084 RAS, dexamethasone-induced 1 6 3266 493 BIRC3 NM_001165 Baculoviral IAP repeat containing 3 5 9536 1882 JUN NM_002228 Jun proto-oncogene 4 10209 2217 EGR1 NM_001964 Early growth response 1 4 19617 4852 BIK NM_001197 BCL2-interacting killer (apoptosis-inducing) 3 2974 1687 TNFAIP3 NM_006290 Tumor necrosis factor, alpha-induced protein 3 3 23395 7931 NR4A2 NM_006186 Nuclear receptor subfamily 4, group A, member 2 3 5256 1822 TFRC NM_003234 Transferrin receptor (p90, CD71) 3 5486 1940 EGR2 NM_000399 Early growth response 2 3 2738 968 SERPINB9 NM_004155 Serpin peptidase inhibitor, clade B (ovalbumin), member 9 2 2948 1109 IFIH1 NM_022168 Interferon induced with helicase C domain 1 2 1712 672 ST6GAL1 NM_173216 ST6 beta-galactosamide alpha-2,6-sialyltranferase 1 2 6789 3307 Genes less strongly expressed in TIL than in PBMC Adhesion ITM2B NM_021999 integral membrane protein 2B -2 5272 2634 ITGB2 NM_000211 integrin, beta 2 -3 19363 6067 PLEK NM_002664 Pleckstrin -4 1862 471 ARRB2 NM_004313 arrestin, beta 2 -4 8774 2186 PXN NM_002859 Paxillin -5 10915 2370 APLP2 NM_001642 amyloid beta (A4) precursor-like protein 2 -5 7460 1465 VCL NM_014000 Vinculin -6 1554 254 PTGER2 NM_000956 prostaglandin E receptor 2 (subtype EP2), 53kDa -6 1567 252 ITGAM NM_000632 integrin, alpha M -7 2077 314 CD33 NM_001772 CD33 molecule -15 1204 80 C5AR1 NM_001736
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    Up-Regulating of RASD1 and Apoptosis of DU-145 Human Prostate Cancer Cells Induced by Formononetin in Vitro

    DOI:http://dx.doi.org/10.7314/APJCP.2014.15.6.2835 Up-regulating of RASD1 and Apoptosis of DU-145 Human Prostate Cancer Cells Induced by Formononetin in Vitro RESEARCH ARTICLE Up-regulating of RASD1 and Apoptosis of DU-145 Human Prostate Cancer Cells Induced by Formononetin in Vitro Xiao-Jia Liu&, Yun-Qian Li&, Qiu-Yue Chen, Sheng-Jun Xiao, Si-En Zeng* Abstract Prostate cancer is one of the most prevalent malignant cancers in men. The isoflavone formononetin is a main active component of red clover plants. In the present study, we assessed the effect of formononetin on human prostate cancer DU-145 cells in vitro, and elucidated posssible mechanisms. DU-145 cells were treated with different concentrations of formononetin and cell proliferation was assessed by MTT assay, cell apoptosis by Hoechst 33258 and flow cytometry, and protein levels of RASD1, Bcl-2 and Bax by Western blotting. The results showed that formononetin inhibited the proliferation of DU-145 cells in a dose-dependent manner. DU-145 cells treated with different concentrations of formononetin displayed obvious morphological changes of apoptosis under fluorescence microscopy. In addition, formononetin increased the proportion of early apoptotic DU-145 cells, down-regulated the protein levels of Bcl-2 and up-regulated those of RASD1 and Bax. The level of RASD1 reached its maximum at 48h post-treatment, and rapidly decreased thereafter. Together, we present evidence that formononetin triggered cell apoptosis through the mitochondrial apoptotic pathway by up-regulating RASD1. Keywords: Formononetin - prostate cancer cells - apoptosis - RASD1 Asian Pac J Cancer Prev, 15 (6), 2835-2839 Introduction which has been wildly used for centuries.
  • Biomarkers, Master Regulators and Genomic Fabric Remodeling in a Case of Papillary Thyroid Carcinoma

    Biomarkers, Master Regulators and Genomic Fabric Remodeling in a Case of Papillary Thyroid Carcinoma

    G C A T T A C G G C A T genes Article Biomarkers, Master Regulators and Genomic Fabric Remodeling in a Case of Papillary Thyroid Carcinoma Dumitru A. Iacobas Personalized Genomics Laboratory, CRI Center for Computational Systems Biology, Roy G Perry College of Engineering, Prairie View A&M University, Prairie View, TX 77446, USA; [email protected]; Tel.: +1-936-261-9926 Received: 1 August 2020; Accepted: 1 September 2020; Published: 2 September 2020 Abstract: Publicly available (own) transcriptomic data have been analyzed to quantify the alteration in functional pathways in thyroid cancer, establish the gene hierarchy, identify potential gene targets and predict the effects of their manipulation. The expression data have been generated by profiling one case of papillary thyroid carcinoma (PTC) and genetically manipulated BCPAP (papillary) and 8505C (anaplastic) human thyroid cancer cell lines. The study used the genomic fabric paradigm that considers the transcriptome as a multi-dimensional mathematical object based on the three independent characteristics that can be derived for each gene from the expression data. We found remarkable remodeling of the thyroid hormone synthesis, cell cycle, oxidative phosphorylation and apoptosis pathways. Serine peptidase inhibitor, Kunitz type, 2 (SPINT2) was identified as the Gene Master Regulator of the investigated PTC. The substantial increase in the expression synergism of SPINT2 with apoptosis genes in the cancer nodule with respect to the surrounding normal tissue (NOR) suggests that SPINT2 experimental overexpression may force the PTC cells into apoptosis with a negligible effect on the NOR cells. The predictive value of the expression coordination for the expression regulation was validated with data from 8505C and BCPAP cell lines before and after lentiviral transfection with DDX19B.