Cancer Biology Research Center

Sioux Falls, SD, United States

Cancer Biology Research Center

Sioux Falls, SD, United States

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News Article | November 16, 2016
Site: www.nature.com

We analysed TCGA data for association between mRNA expression level of 16 candidate immune-related genes (ARG1, IL10, FOXP3, CD68, IL12A, IL12B, IFNG, CD8A, CD4, ITGAM (also known as CD11B), CD14, TNF, IL1A, IL1B, IL6 and CCL5) and 5 year overall survival. Illumina HiSeq RNaseqV2 mRNA expression and clinical data for 520 head and neck squamous cell carcinoma samples were downloaded from the TCGA data portal. Median follow-up from diagnosis was 1.8 years with a range of 0.01 years to 17.6 years. Follow-up time was truncated at 5-years for analysis and 200 deaths occurred in this period. For each of the 16 candidate immune response genes, we scored subjects as above (high) or below (low) the median expression and compared survival using a log-rank test at 5% significance. HPV+ patients were stratified into a favourable immune profile if they had expression above the median for the significant genes IL12A, IL12B, IFNG, CD8A and below the median for IL6. Kaplan–Meier curves were plotted for these two groups. Similar methods were used to examine association of these 16 genes with 720 lung adenocarcinoma and 876 gastric carcinoma samples using the publically available data from KM Plotter29. In lung adenocarcinomas, 12 genes were significantly associated with survival; patients were scored as having a favourable immune profile if 7 or more of the 12 significant genes had expression in the favourable direction. In 876 gastric cancer samples, 8 genes were significantly associated with survival. Patients were scored as having a favourable immune profile if 5 out of the 8 genes had expression in the favourable direction. We investigated 66 immune-related genes in four functional classes, 17 genes related to antigen presentation (HLA class I and II molecules), 24 genes surveying T cell activation, 20 innate immune response genes (IL6, CCL7 and others) and 5 genes related to cancer cell signalling. These genes changed expression in response to PI3Kγ inhibition for association with survival in HPV+ and HPV− TCGA HNSCC and lung adenocarcinoma cohorts. Within each cancer type, we scored subjects as above or below the median expression for each gene and compared survival using a log-rank test, using 10% false discovery rate (FDR) within each class as the significance threshold. HPV+ and HPV− HNSCC survival were investigated separately, as HPV− HNSCC generally has a worse prognosis. Within each cohort, patients were classified as having a favourable PI3Kγ immune response profile if they had expression levels above or below the median in the direction of low PI3Kγ activity for the genes identified as significant. We compared the survival experience of favourable versus less-favourable profiles of patients using Kaplan–Meier curves. Out of the 66 experimentally identified PI3Kγ-regulated genes, 43 showed significant association with overall survival in the HPV+ cohort (FDR < 10% within each functional class). Comparison of these genes between HPV+ and HPV− cohorts showed that HPV− samples generally had significantly (P < 0.05) lower expression of 42 genes in the antigen presentation and T cell activation classes, consistent with a pattern of adaptive immune suppression, and higher expression of genes in the innate immune response and cancer cell signalling classes, which were negatively associated with survival. Only MALT1 was not differentially expressed between the two groups (P = 0.7). Pik3cg−/− and Pik3cg−/−,PyMT mice were generated as previously described13. Cd8−/− and Cd4−/− mice with a C57Bl/6J background were purchased from the Jackson Laboratory and crossed with syngeneic Pik3cg−/− mice. All animal experiments were performed with approval from the Institutional Animal Care and Use Committee of the University of California. Animals were euthanized before the IACUC maximum allowable tumour burden of 2 cm3 per mouse was exceeded. Wild-type or Pik3cg−/− 6–8 week-old female or male syngeneic C57Bl/6J (LLC lung, PyMT breast and MEER HPV+ HNSCC) or C3He/J (SSCVII HPV− HNSCC) mice were implanted with 106 tumour cells by subcutaneous injection (LLC, MEER, SCCVII) or by orthotopic injection (PyMT) (n = 10–15) and tumour growth was monitored for up to 30 days. Tumour dimensions were measured once when tumours were palpable. Tumour volumes were calculated using the equation (l2 × w)/2. In some studies, wild-type and Pik3cg−/− mice with LLC tumours were treated with gemcitabine (150 mg kg−1) or saline by intraperitoneal (i.p.) injection on day 7 and day 14 (n = 10). LLC were acquired from ATCC, PyMT were from L. Ellies (University of California), HPV+ MEER were from J. Lee (Cancer Biology Research Center, Sanford Research/USD) and SCCVII squamous carcinoma cells were from S. Schoenberger (La Jolla Institute for Allergy and Immunology). All cell lines were tested for mycoplasma and mouse pathogens and checked for authenticity against the International Cell Line Authentication Committee (ICLAC; http://iclac.org/databases/cross-contaminations/) list. In some studies, mice bearing LLC, PyMT, HPV+ MEER or HPV− HNSCC tumour cells were treated once daily by oral gavage with vehicle (5% NMP and 95% PEG 400), 15 mg kg−1 per day of the PI3Kγ inhibitor IPI-549 or by i.p. injection with 2.5 mg kg−1 twice per day of TG100-115 (ref. 13) beginning on day 8 post-tumour injection and continuing daily until euthanasia. IPI-549 is an orally bioavailable PI3Kγ inhibitor with a long plasma half-life and a K value of 0.29 nM for PI3Kγ with >58-fold weaker binding affinity for the other class I PI3K isoforms17. Enzymatic and cellular assays confirmed the selectivity of IPI-549 for PI3Kγ (>200-fold in enzymatic assays and >140-fold in cellular assays over other class I PI3K isoforms17). To study the effect of IPI-549 on lung tumour growth, LLC tumour cells were passaged three times in C57BL/6 albino male mice. When tumour volume reached 1,500 mm3, tumours were collected and single-cell suspensions were prepared. This tumour cell suspension was implanted subcutaneously in the hind flank of C57BL/6 albino male mice at 106 cells per mouse. Prior to initiating treatment with once daily IPI-549 (15 mg kg−1 orally), groups were normalized on the basis of tumour volume. In some studies, wild-type- and Pik3cg−/−-tumour-bearing mice were treated with 100 μg of anti-CD8 (clone YTS 169.4) or an isotype-control clone (LTF-2) from Bio X Cell administered by i.p. injections on day 7, 10 and 13 of tumour growth. For all tumour experiments, tumour volumes and weights were recorded at death. C57Bl/6J (wild-type) or Pik3cg−/− 6–8 week-old male or female mice (MEER HPV+ HNSCC) or C3He/J (SCCVII HPV− HNSCC) were implanted with tumour cells by subcutaneous injection (106 MEER or 105 SCCVII). In HPV+ MEER studies, wild-type and Pik3cg−/− mice were treated with four doses of 250 μg of anti-PD-1 antibody (clone RMP-14, Bio X Cell) or rat IgG2a isotype control (clone 2A3, Bio X Cell) every 3 days, starting when tumours became palpable on day 11 (n = 12–14 mice per group). Wild-type mice bearing HPV+ tumours were also treated with the PI3Kγ inhibitor TG100-115 (ref. 13) twice per day by i.p. injection, beginning on day 11. Tumour regressions were calculated as a percentage of the difference in tumour volume between the date treatment was initiated and the first date of death of the control group. For HPV− SCCVII studies, C3He/J mice were treated with PI3Kγ inhibitor (2.5 mg kg−1 TG100-115 i.p.) beginning on day 6 post-tumour inoculation and with six doses of anti-PD-1 antibody (250 μg clone RMP-14, Bio X Cell) or rat IgG2a isotype control (clone 2A3, Bio X Cell) every 3 days beginning on day 3 (n = 12 mice per group) or with a combination of the two. Alternatively, mice were treated with 5 mg kg−1 TG100-115 twice per day ± anti-PD-1 (250 μg every 3 days) beginning on day 1 (Fig. 4). Mice that completely cleared HPV+ MEER tumours were re-injected with HPV+ tumour cells contralateral to the initial tumour injection and tumour growth was monitored. The growth and metastasis of spontaneous mammary tumours in female PyMT+ (n = 13) and Pik3cg−/−,PyMT+ (n = 8) mice was evaluated over the course of 0–15 weeks. Total tumour burden was determined by subtracting the total mammary gland mass in PyMT− mice from the total mammary gland mass in PyMT+ mice. Lung metastases were quantified macroscopically and microscopically in H&E tissue sections at week 15. Septic shock was induced in wild-type and Pik3cg−/− mice via i.p. injection of 25 mg kg−1 LPS (Sigma, B5:005). Survival was monitored every 12 h and liver, bone marrow and serum were collected 24 h after LPS injection. C57Bl/6J female mice were implanted with 106 LLC tumour cells by subcutaneous injection. When the average tumour size was 250 mm3, mice were treated by i.p. injection with 1 mg per mouse clodronate or control liposomes (www.clodronateliposomes.com) every 4 days for 2 weeks in combination with daily administration of vehicle or IPI-549 (15 mg kg−1 per day orally). In other studies, 6-week-old female BALB/c mice were injected subcutaneously with 2.5 × 105 CT26 mouse colon carcinoma cells in 100 μl phosphate buffered saline (PBS) in the right flank. Eight days later, tumour-bearing mice were arranged into four groups (n = 15) with an average tumour volume of 70 mm3. Oral administration of IPI-549 (15 mg kg−1) or vehicle (5% NMP and 95% PEG 400) and anti-CSF-1R antibody (50 mg kg−1 i.p. 3× per week, clone AFS98, Bio X Cell) began on day 8 after tumour injection via oral gavage at a 5 ml kg−1 dose volume and continued daily for a total of 18 doses. Six-week-old female BALC/c mice were injected subcutaneously with 2.5 × 105 CT26 mouse colon carcinoma cells in 100 μl PBS in the right flank. On day 8 after tumour injection, tumour-bearing mice were grouped and treated daily with IPI-549 (15 mg kg−1, orally) or vehicle (5%NMP and 95% PEG 400). In addition, mice were injected i.p. with 50 mg kg−1 anti-CD115 (Bio X Cell clone AFS98) or 50 mg kg−1 rat IgG2a isotype control (Bio X Cell clone 2A3) antibodies as described above for a total of three injections. Two days after the final injection mice were euthanized, tumours were digested in a mixture of 0.5 mg ml−1 collagenase IV and 150 U ml−1 DNase I in RPMI-1640 for 30 min at 37 °C and tumour-infiltrating myeloid cells were analysed by flow cytometry. CD11b+Gr1− cells were isolated from single-cell suspensions of LLC tumours from donor mice by fluorescence-activated cell sorting (FACS) or serial magnetic bead isolation. Additionally, for some experiments, primary bone-marrow-derived macrophages were polarized and collected into a single-cell suspension. Purified cells were admixed 1:1 with LLC tumour cells and 5 × 105 total cells were injected subcutaneously into new host mice. Tumour dimensions were measured three times per week beginning on day 7. In antibody blocking studies, CD11b+Gr1− cells were incubated with 5 μg anti-IL12 (clone RD1-5D9) or isotype (clone LTF-2, Bio X Cell) for 30 min before the addition of tumour cells. Mice were additionally treated intradermally with 5 μg of antibody 3 and 6 days after tumour cell inoculation. In some studies, CD11b+Gr1− cells were pre-incubated with inhibitors of arginase (nor-NOHA, 50 μM, Cayman Chemical), iNOS (1400W dihydrocholoride, 100 μM, Tocris), mTOR (rapamycin, 10 μM Calbiochem), or IκKβ (ML120B, 30 μM, Tocris) for 30 min before the addition of tumour cells. Inoculated mice were further treated by intradermal injection with inhibitors at 3 and 6 days after inoculation. Donor C57Bl/6J (WT) or Pik3cg−/− mice were implanted with 106 LLC tumour cells by subcutaneous injection. On day 14 after tumour implantation, CD90.2+, CD4+ or CD8+ cells were harvested by magnetic bead isolation (Miltenyi Biotec). T cells were mixed 1:1 with viable LLC tumour cells. Cell mixtures containing 5 × 105 total cells were injected into the flanks of naive wild-type or Pik3cg−/− mice (n = 8–10 per group). Tumour growth, intratumoral apoptosis and necrosis were investigated over 0–16 days. In other studies, wild-type T cells were incubated at 37 °C and 5% CO for 6 h with 10 or 100 nM IPI-549 (Infinity Pharmaceuticals) or Cal-101 (Selleck Chem). After 6 h, T cells were washed, admixed 1:1 with LLC tumour cells, and 106 total cells were injected subcutaneously into recipient mice. Tumour growth was monitored for 14 days. Tumours were isolated, minced in a Petri dish on ice and then enzymatically dissociated in Hanks balanced salt solution containing 0.5 mg ml−1 collagenase IV (Sigma), 0.1 mg ml−1 hyaluronidase V (Sigma), 0.6 U ml−1 dispase II (Roche) and 0.005 MU ml−1 DNase I (Sigma) at 37 °C for 5–30 min. The duration of enzymatic treatment was optimized for greatest yield of live CD11b+ cells per tumour type. Cell suspensions were filtered through a 70-μm cell strainer. Red blood cells were solubilized with red cell lysis buffer (Pharm Lyse, BD Biosciences) and the resulting suspension was filtered through a cell strainer to produce a single-cell suspension. Cells were washed once with PBS before use in flow cytometry analysis or magnetic bead purification. Thioglycollate-elicited peritoneal macrophages were collected 96 h after i.p. injection of a 3% thioglycollate solution. Cells were collected from the peritoneal cavity in 10 ml of PBS and macrophage enrichment was performed by plating cells in RPMI with 10% FBS and 1% penicillin/streptomycin for 2 h at 37 °C and 5% CO . After 2 h, non-adherent cells were removed with three PBS washes, and cells were analysed via flow cytometry and qPCR analysis. Single-cell suspensions (106 cells in 100 μl total volume) were incubated with aqua live dead fixable stain (Life Technologies), FcR-blocking reagent (BD Biosciences) and fluorescently labelled antibodies and incubated at 4 °C for 1 h. Primary antibodies to cell surface markers directed against F4/80 (BM8), CD45 (30-F11), CD11b (M1/70), Gr1 (RB6-8C5), CD3 (145-2C11), CD4 (GK1.5), CD8 (53-6.7), CD273 (B7-DC), CD274 (B7-H1) were from eBioscience; Ly6C (AL-21), Ly6G (1A8), CD11c (HL3), and MHC-II (AF6-120.1) from BD Pharmingen, CCR2 (475301) from R&D Systems and CD206 (MR5D3) from AbD Serotech. For intracellular staining, cells were fixed, permeabilized using transcription factor staining buffer set (eBioscience) and then incubated with fluorescently labelled antibodies to FoxP3 (FJK-16 s) from eBioscience. Multicolour FACS analysis was performed on a BD Canto RUO 11 colour analyser. All data analysis was performed using the flow cytometry analysis program FloJo (Treestar). Single-cell preparations from bone marrow or tumours were incubated with FcR-blocking reagent (BD Biosciences) and then with 20 μl magnetic microbeads conjugated to antibodies against CD11b, Gr1, CD90.2, CD4 and CD8 (Miltenyi Biotech MACS Microbeads) per 107 cells for 20 min at 4 °C. Cells bound to magnetic beads were then removed from the cell suspension according to the manufacturer’s instructions. For cell sorting, single-cell suspensions were stained with aqua live dead fixable stain (Life Technologies) to exclude dead cells and anti-CD11b-APC (M1/70, eBioscience) and anti-Gr1-FITC (RB6-8C5, eBioscience) antibodies. FACS sorting was performed on a FACS Aria 11 colour high speed sorter at the Flow Cytometry Core at the UC San Diego Center for AIDS Research. Live cells were sorted into the following populations: CD11b+Gr1−, CD11b+Gr1lo, CD11b+Gr1hi and CD11b−Gr1− cells. CD11b-positive cells were defined by increased staining over the isotype control, and Gr1 levels were defined both by comparison to the isotype control and relative staining to other populations. Bone-marrow-derived cells were aseptically collected from 6–8 week-old female mice by flushing leg bones of euthanized mice with PBS, 0.5% BSA, 2 mM EDTA, incubating in red cell lysis buffer (155 mM NH Cl, 10 mM NaHCO and 0.1 mM EDTA) and centrifuging over Histopaque 1083 to purify the mononuclear cells. Approximately 5 × 107 bone-marrow-derived cells were purified by gradient centrifugation from the femurs and tibias of a single mouse. Purified mononuclear cells were cultured in RPMI + 20% serum + 50 ng ml−1 mCSF (PeproTech). Human leukocytes from apheresis blood products were obtained from the San Diego Blood Bank. Cells were diluted in PBS, 0.5% BSA, 2 mM EDTA, incubated in red cell lysis buffer (155 mM NH Cl, 10 mM NaHCO and 0.1 mM EDTA) and centrifuged over Histopaque 1077 to purify mononuclear cells. Approximately 109 bone-marrow-derived cells were purified by gradient centrifugation from one apheresis sample. Purified mononuclear cells were cultured in RPMI + 20% serum + 50 ng ml−1 Human mCSF (PeproTech). Non-adherent cells were removed after 2 h by washing and adherent cells were cultured for 6 days to differentiate macrophages fully. Bone-marrow-derived macrophages were polarized with IFNγ (20 ng ml−1, Peprotech) + LPS (100 ng ml−1, Sigma) or LPS alone for 24 h, or IL4 (20 ng ml−1, Peprotech) for 24–48 h. For inhibitor studies, PI3Kγ inhibitors (1 μM) (IPI-549, Infinity Pharmaceuticals and TG100-115, Targegen/Sanofi-Aventis), rapamycin (10 μM, Selleck), or ML120B (30 μM) were incubated with macrophages 1 h before the addition of polarizing stimuli. Total RNA was harvested from macrophages using the RNeasy Mini Kit (Qiagen) according to the manufacturer’s instructions. Freshly isolated mouse bone marrow cells from nine wild-type and nine Pik3cg−/− mice were pooled into three replicates sets of wild-type or Pik3cg−/− cells and differentiated into macrophages for 6 days in RPMI + 20% FBS+ 1% penicillin/streptomycin + 50 ng ml−1 mCSF. Each replicate set of macrophages was then treated with mCSF, IL4 or IFNγ/LPS. Macrophages were removed from dishes, and RNA was collected using Qiagen Allprep kit. In addition, RNA was harvested from day 14 (500 mm3) LLC tumours or purified CD11b+Gr1-F480+ TAMs from wild-type (C57BL/6) and Pik3cg−/− mice. RNA was collected using the Qiagen Allprep kit. RNA libraries were prepared from 1 μg RNA per sample for sequencing using standard Illumina protocols. RNA sequencing was performed by the University of California, San Diego Institute for Genomic Medicine. mRNA profiles were generated by single read deep sequencing, in triplicate, using Illumina HiSeq2000. Sequence analysis was performed as previously described16. Sequence files from Illumina HiSeq that passed quality filters were aligned to the mouse transcriptome (mm9 genome build) using the Bowtie2 aligner4. Gene-level count summaries were analysed for statistically significant changes using DESeq. Individual P values were adjusted for multiple testing by calculating Storey’s q values using fdrtooltrimmer. For each gene, the q value is the smallest false discovery rate at which the gene is found significant. We analysed biological processes as defined by the Gene Ontology Consortium. Each gene ontology term defines a set of genes. The entire list of genes, sorted by the q value in ascending order, was subjected to a non-parametric variant of the gene set enrichment analysis (GSEA), in which the parametric Kolmogorov–Smirnov P value was replaced with the exact rank-order P value. We perform a Bonferroni adjustment of gene set P values for the number of gene sets tested. Heat maps of expression levels were created using in-house hierarchical clustering software that implements Ward clustering. The colours qualitatively correspond to fold changes. cDNA was prepared using 1 μg RNA with the qScript cDNA Synthesis Kit (Quanta Biosciences). Sybr green-based qPCR was performed using human and mouse primers to Arg1, Ifng, Il10, Il12p40, Il1b, Il6, Ccl2, Vegfa, Gapdh, Nos2, Tgfb1, Tnfa and mouse H2-Aa, H2-Ab1, H2-Eb1, and H60a (Qiagen QuantiTect Primer Assay). mRNA levels were normalized to Gapdh and reported as relative mRNA expression or fold change. Freshly isolated bone-marrow-derived CD11b+ myeloid cells or differentiated macrophages were transfected by electroporation using an AMAXA mouse macrophage nucleofection kit with 100 nM of siRNA or 2 μg Pik3cgCAAX or pcDNA control plasmid. Non-silencing (Ctrl_AllStars_1) siRNA and Cebpb (MmCebpb_4 and MmCebpb_6), and Mtor (Mm_Frap1_1 and Mm_Frap1_2) siRNAs were purchased from Qiagen. After transfection, cells were cultured for 36–48 h in RPMI containing 10% serum and 10 ng ml−1 mCSF (PeproTech) or polarized as described above. Whole tumours, CD11b+Gr1− cells, CD90.2+ cells, CD4+ cells and CD8+ cells isolated from LLC tumours were lysed in RIPA buffer and total protein concentrations were determined using a BCA protein assay (Pierce). Macrophage supernatants (100 μl) or 500 μg of total protein lysate from tumours were used in ELISAs to detect CCL2, TGFβ, IL1β, TNFα, IL6, IFNγ, IL10, IL12 and granzyme B (ready set go ELISA, eBioscience). Protein expression was normalized to total volume (supernatants) or mg total protein (tumour lysates). The QuantiChrom arginase assay kit (DARG-200, BioAssay Systems) was used to measure arginase activity in primary mouse bone-marrow-derived macrophages from wild-type and Pik3cg−/− mice according to the manufacturer’s instructions. For all conditions, cells were harvested and lysed in 10 mM Tris (pH 7.4) containing 1 μM pepstatin A, 1 μM leupeptin, and 0.4% (w/v) Triton X-100. Samples were centrifuged at 20,000g at 4 °C for 10 min. To measure NFκB and C/EBPβ activation, TransAM NFκB family and C/EBP transcription factor assay kits (43296 and 44196, Active Motif) were used according to the manufacturer’s protocol. Briefly, wild-type and Pik3cg−/− bone-marrow-derived macrophages were stimulated with LPS (100 ng ml−1) or IL4 (20 ng ml−1) and nuclear extracts were prepared in lysis buffer AM2 (Active Motif). Nuclear extracts were incubated with the immobilized consensus sequences and RelA, cRel or C/EBPβ were detected using specific primary antibodies. Quantification was performed via colourimetric readout of absorbance at 450 nm. IL4 and LPS macrophage cultures were solubilized in RIPA buffer containing protease and phosphatase inhibitors. Thirty micrograms of protein was electrophorezed on Biorad precast gradient gels and electroblotted onto PVDF membranes. Proteins were detected by incubation with 1:1,000 dilutions of primary antibodies, washed and incubated with goat anti-rabbit-HRP antibodies and detected after incubation with a chemiluminescent substrate. Primary antibodies directed against Akt (11E7), p-Akt (244F9), IκBα (L35A5), IκKβ (D30C6), p-IκKα/β (16A6), RelA (D14E12), pRelA (93H1), C/EBPβ (#3087), p-CEBPβ (#3082), IRAK1 (D51G7), TBK1 (D1B4) and PI3Kγ (#4252) were from Cell Signaling Technology and pTBK1 (EPR2867(2)) was from Abcam. CD90.2+ tumour-derived T cells were purified from LLC tumour-bearing wild-type and Pik3cg−/− or TG100-115 and control treated mice and then co-incubated with LLC tumour cells (target cells) at 2.5:1, 5:1 and 10:1 ratios of T cells to tumour cells (2 × 103 LLC tumour cells per well) for 6 h. Target cell killing was assayed by collecting the supernatants from each well for measurement of the lactate dehydrogenase release (Cytotox96 non-radioactive cytotoxicity assay kit, Promega). Tumour samples were collected and cryopreserved in OCT, sections (5 μm) were fixed in 100% cold acetone, blocked with 8% normal goat serum for 2 h, and incubated anti-CD8 (53-6.7, 1:50 BD Biosciences) for 2 h at room temperature. Sections were washed three times with PBS and incubated with Alexa594-conjugated secondary antibodies. Slides were counterstained with 4′,6-diamidino-2-phenylindole (DAPI) to identify nuclei. Immunofluorescence images were collected on a Nikon microscope (Eclipse TE2000-U) and analysed using Metamorph image capture and analysis software (Version 6.3r5, Molecular Devices). The detection of apoptotic cells was performed using a TUNEL-assay (ApopTag fluorescein in situ apoptosis detection kit, Promega) according to the manufacturer’s instructions. Slides were washed and mounted in DAKO fluorescent mounting medium. Immunofluorescence images were collected on a Nikon microscope (Eclipse TE2000-U) and analysed with MetaMorph software (version 6.3r5) or SPOT software (version 4.6). Pixels per field or cell number per field were quantified in five 100× fields from ten biological replicates. Primary tumour samples with mRNA expression data were scored as above or below the median expression level, and tested for association with patient survival using a log-rank test at 5% significance. For studies evaluating the effect of drugs on tumour size, tumour dimensions were measured directly before the start of treatment, tumour volumes were computed and mice were randomly assigned to groups so that the mean volume ± s.e.m. of each group was identical. A sample size of ten mice per group provided 80% power to detect a mean difference of 2.25 standard deviation (s.d.) between two groups (based on a two-sample t-test with two-sided 5% significance level). Sample sizes of 15 mice per group provided 80% power to detect one s.d. difference between two groups. Data were normalized to the standard (control). Analysis for significance was performed by one-way ANOVA with a Tukey’s post-hoc test for multiple pairwise testing with more than two groups and by parametric or nonparametric Student’s t-test when only two groups were compared. We used a two-sample t-test (two groups) and ANOVA (multiple groups) when data were normally distributed and a Wilcoxon rank sum test (two groups) when data were not normally distributed. All mouse studies were randomized and blinded; assignment of mice to treatment groups, tumour measurement and tumour analysis was performed by coding mice with randomly assigned mouse number, with the key unknown to operators until experiments were completed. In tumour studies for which tumour size was the outcome, mice removed from the study owing to health concerns were not included in endpoint analyses. All experiments were performed at least twice; n refers to biological replicates. RNA sequencing data can be accessed using numbers GSE58318 (in vitro macrophage samples) and GSE84535 (in vivo tumour and tumour-associated macrophages samples) at www.ncbi.nlm.nih.gov/geo.


Dhuban K.B.,McGill University | D'Henneze E.,McGill University | Nashi E.,McGill University | Bar-Or A.,Montreal Neurological Institute | And 4 more authors.
Journal of Immunology | Year: 2015

Two distinct subsets of CD4+Foxp3+ regulatory T (Treg) cells have been described based on the differential expression of Helios, a transcription factor of the Ikaros family. Efforts to understand the origin and biological roles of these Treg populations in regulating immune responses have, however, been hindered by the lack of reliable surface markers to distinguish and isolate them for subsequent functional studies. Using a single-cell cloning strategy coupled with microarray analysis of different Treg functional subsets in humans, we identify the mRNA and protein expression of TIGIT and FCRL3 as a novel surface marker combination that distinguishes Helios+FOXP3+ from Helios-FOXP3+ memory cells. Unlike conventional markers that are modulated on conventional T cells upon activation, we show that the TIGIT/FCRL3 combination allows reliable identification of Helios+ Treg cells even in highly activated conditions in vitro as well as in PBMCs of autoimmune patients. We also demonstrate that the Helios-FOXP3+ Treg subpopulation harbors a larger proportion of nonsuppressive clones compared with the Helios+ FOXP3+ cell subset, which is highly enriched for suppressive clones. Moreover, we find that Helios- cells are exclusively responsible for the productions of the inflammatory cytokines IFN-γ, IL-2, and IL-17 in FOXP3+ cells ex vivo, highlighting important functional differences between Helios+ and Helios- Treg cells. Thus, we identify novel surface markers for the consistent identification and isolation of Helios+ and Helios- memory Treg cells in health and disease, and we further reveal functional differences between these two populations. These new markers should facilitate further elucidation of the functional roles of Heliosbased Treg heterogeneity. Copyright © 2015 by The American Association of Immunologists, Inc. 0022-1767/15/$25.00.


Yallapu M.M.,Cancer Biology Research Center | Jaggi M.,Cancer Biology Research Center | Jaggi M.,University of South Dakota | Chauhan S.C.,Cancer Biology Research Center | Chauhan S.C.,University of South Dakota
Colloids and Surfaces B: Biointerfaces | Year: 2010

Curcumin, a hydrophobic polyphenolic compound derived from the rhizome of the herb Curcuma longa, possesses a wide range of biological applications including cancer therapy. However, its prominent application in cancer treatment is limited due to sub-optimal pharmacokinetics and poor bioavailability at the tumor site. In order to improve its hydrophilic and drug delivery characteristics, we have developed a β-cyclodextrin (CD) mediated curcumin drug delivery system via encapsulation technique. Curcumin encapsulation into the CD cavity was achieved by inclusion complex mechanism. Curcumin encapsulation efficiency was improved by increasing the ratio of curcumin to CD. The formations of CD-curcumin complexes were characterized by Fourier transform infrared (FTIR), differential scanning calorimetry (DSC), thermo-gravimetric analysis (TGA), scanning electron microscope (SEM), and transmission electron microscope (TEM) analyses. An optimized CD-curcumin complex (CD30) was evaluated for intracellular uptake and anti-cancer activity. Cell proliferation and clonogenic assays demonstrated that β-cyclodextrin-curcumin self-assembly enhanced curcumin delivery and improved its therapeutic efficacy in prostate cancer cells compared to free curcumin. © 2010 Elsevier B.V.


Zheng Y.,Cancer Biology Research Center | Zheng Y.,University of South Dakota | Zheng Y.,University of Houston | Miskimins W.K.,Cancer Biology Research Center
RNA Biology | Year: 2011

The cyclin dependent kinase inhibitor p27 Kip1 plays an important role in controlling the eukaryotic cell cycle. The 5′-untranslated region of the p27 mRNA harbors an internal ribosome entry site (IRES ) which may facilitate synthesis of p27 in certain conditions. In this study, the RNA-associated protein CU GBP1 was shown to interact with the human p27 5′-untranslated region. Overexpression of CU GBP1 inhibited endogenous p27 expression and reduced translation initiation through the p27 IRES . In contrast, repression of CU GBP1 by siRNA transfection enhanced p27 protein levels and stimulated p27 IRES activity. Addition of recombinant CU GBP1 repressed p27 IRES reporter mRNA translation in vitro. At last, our finding showed that cytosolic form of CU GBP1 binds efficiently to the p27 5′-untranslated region. © 2011 Landes Bioscience.


Zhuang Y.,Cancer Biology Research Center | Miskimins W.K.,Cancer Biology Research Center | Miskimins W.K.,University of South Dakota
Molecular Cancer Research | Year: 2011

There is substantial evidence that metformin, a drug used to treat type 2 diabetics, is potentially useful as a therapeutic agent for cancer. However, a better understanding of the molecular mechanisms through which metformin promotes cell-cycle arrest and cell death of cancer cells is necessary. It will also be important to understand how the response of tumor cells differs from normal cells and why some tumor cells are resistant to the effects of metformin. We have found that exposure to metformin induces cell death in all but one line, MDA-MB-231, in a panel of breast cancer cell lines.MCF10A nontransformed breast epithelial cells were resistant to the cytotoxic effects of metformin, even after extended exposure to the drug. In sensitive lines, cell death was mediated by both apoptosis and a caspase-independent mechanism. The caspase-independent pathway involves activation of poly(ADP-ribose) polymerase (PARP) and correlates with enhanced synthesis of PARP and nuclear translocation of apoptosis-inducing factor (AIF), which plays an important role in mediating cell death. Metformin-induced, PARP-dependent cell death is associated with a striking enlargement of mitochondria. Mitochondrial enlargement was observed in all sensitive breast cancer cell lines but not in nontransformed cells or resistant MDA-MB-231. Mitochondrial enlargement was prevented by inhibiting PARP activity or expression. A caspase inhibitor blocked metformin-induced apoptosis but did not affect PARP-dependent cell death or mitochondrial enlargement. Thus, metformin has cytotoxic effects on breast cancer cells through 2 independent pathways. These findings will be pertinent to efforts directed at using metformin or related compounds for cancer therapy. ©2011 AACR.


Chan D.K.,Cancer Biology Research Center | Miskimins W.K.,Cancer Biology Research Center
Journal of Ovarian Research | Year: 2012

Background: High mortality rates in ovarian cancer are largely a result of resistance to currently used chemotherapies. Expanding therapies with a variety of drugs has the potential to reduce this high mortality rate. Metformin and phenethyl isothiocyanate (PEITC) are both potentially useful in ovarian cancer, and they are particularly attractive because of their safety. Methods. Cell proliferation of each drug and drug combination was evaluated by hemacytometry with Trypan blue exclusion or Sytox green staining for cell death. Levels of total and cleaved PARP were measured by Western blot. General cellular and mitochondrial reactive oxygen species were measured by flow cytometry and live cell confocal microscopy with the fluorescent dyes dihydroethidine and MitoSOX. Results: Individually, metformin and PEITC each show inhibition of cell growth in multiple ovarian cancer cell lines. Alone, PEITC was also able to induce apoptosis, whereas metformin was primarily growth inhibitory. Both total cellular and mitochondrial reactive oxygen species were increased when treated with either metformin or PEITC. The growth inhibitory effects of metformin were reversed by methyl succinate supplementation, suggesting complex I plays a role in metformin's anti-cancer mechanism. PEITC's anti-cancer effect was reversed by N-acetyl-cysteine supplementation, suggesting PEITC relies on reactive oxygen species generation to induce apoptosis. Metformin and PEITC together showed a synergistic effect on ovarian cancer cell lines, including the cisplatin resistant A2780cis. Conclusions: Here we show that when used in combination, these drugs are effective in both slowing cancer cell growth and killing ovarian cancer cells in vitro. Furthermore, the combination of these drugs remains effective in cisplatin resistant cell lines. Novel combinations such as metformin and PEITC show promise in expanding ovarian cancer therapies and overcoming the high incidence of cisplatin resistant cancers. © 2012Chan and Miskimins;licensee BioMed Central Ltd.


Sundram V.,Cancer Biology Research Center | Chauhan S.C.,Cancer Biology Research Center | Chauhan S.C.,University of South Dakota | Jaggi M.,Cancer Biology Research Center | Jaggi M.,University of South Dakota
Molecular Cancer Research | Year: 2011

Protein kinase D1 (PKD1) is a serine-threonine kinase that regulates various functions within the cell, including cell proliferation, apoptosis, adhesion, and cell motility. In normal cells, this protein plays key roles in multiple signaling pathways by relaying information from the extracellular environment and/or upstream kinases and converting them into a regulated intracellular response. The aberrant expression of PKD1 is associated with enhanced cancer phenotypes, such as deregulated cell proliferation, survival, motility, and epithelial mesenchymal transition. In this review, we summarize the structural and functional aspects of PKD1 and highlight the pathobiological roles of this kinase in cancer. ©2011 AACR.


Sundram V.,Cancer Biology Research Center | Chauhan S.C.,Cancer Biology Research Center | Chauhan S.C.,University of South Dakota | Ebeling M.,Cancer Biology Research Center | And 2 more authors.
PLoS ONE | Year: 2012

Prostate cancer is the most commonly diagnosed cancer affecting 1 in 6 males in the US. Understanding the molecular basis of prostate cancer progression can serve as a tool for early diagnosis and development of novel treatment strategies for this disease. Protein Kinase D1 (PKD1) is a multifunctional kinase that is highly expressed in normal prostate. The decreased expression of PKD1 has been associated with the progression of prostate cancer. Therefore, synthetic or natural products that regulate this signaling pathway can serve as novel therapeutic modalities for prostate cancer prevention and treatment. Curcumin, the active ingredient of turmeric, has shown anti-cancer properties via modulation of a number of different molecular pathways. Herein, we have demonstrated that curcumin activates PKD1, resulting in changes in β-catenin signaling by inhibiting nuclear β-catenin transcription activity and enhancing the levels of membrane β-catenin in prostate cancer cells. Modulation of these cellular events by curcumin correlated with decreased cell proliferation, colony formation and cell motility and enhanced cell-cell aggregation in prostate cancer cells. In addition, we have also revealed that inhibition of cell motility by curcumin is mediated by decreasing the levels of active cofilin, a downstream target of PKD1. The potent anti-cancer effects of curcumin in vitro were also reflected in a prostate cancer xenograft mouse model. The in vivo inhibition of tumor growth also correlated with enhanced membrane localization of β-catenin. Overall, our findings herein have revealed a novel molecular mechanism of curcumin action via the activation of PKD1 in prostate cancer cells. © 2012 Sundram et al.


Haugrud A.B.,Cancer Biology Research Center | Zhuang Y.,Cancer Biology Research Center | Coppock J.D.,Cancer Biology Research Center | Miskimins W.K.,Cancer Biology Research Center
Breast Cancer Research and Treatment | Year: 2014

The unique metabolism of breast cancer cells provides interest in exploiting this phenomenon therapeutically. Metformin, a promising breast cancer therapeutic, targets complex I of the electron transport chain leading to an accumulation of reactive oxygen species (ROS) that eventually lead to cell death. Inhibition of complex I leads to lactate production, a metabolic byproduct already highly produced by reprogrammed cancer cells and associated with a poor prognosis. While metformin remains a promising cancer therapeutic, we sought a complementary agent to increase apoptotic promoting effects of metformin while attenuating lactate production possibly leading to greatly improved efficacy. Dichloroacetate (DCA) is a well-established drug used in the treatment of lactic acidosis which functions through inhibition of pyruvate dehydrogenase kinase (PDK) promoting mitochondrial metabolism. Our purpose was to examine the synergy and mechanisms by which these two drugs kill breast cancer cells. Cell lines were subjected to the indicated treatments and analyzed for cell death and various aspects of metabolism. Cell death and ROS production were analyzed using flow cytometry, Western blot analysis, and cell counting methods. Images of cells were taken with phase contrast microscopy or confocal microscopy. Metabolism of cells was analyzed using the Seahorse XF24 analyzer, lactate assays, and pH analysis. We show that when DCA and metformin are used in combination, synergistic induction of apoptosis of breast cancer cells occurs. Metformin-induced oxidative damage is enhanced by DCA through PDK1 inhibition which also diminishes metformin promoted lactate production. We demonstrate that DCA and metformin combine to synergistically induce caspase-dependent apoptosis involving oxidative damage with simultaneous attenuation of metformin promoted lactate production. Innovative combinations such as metformin and DCA show promise in expanding breast cancer therapies. © 2014, Springer Science+Business Media New York.


Yallapu M.M.,Cancer Biology Research Center | Gupta B.K.,Cancer Biology Research Center | Jaggi M.,Cancer Biology Research Center | Jaggi M.,University of South Dakota | And 2 more authors.
Journal of Colloid and Interface Science | Year: 2010

Curcumin, a natural polyphenolic compound, has shown promising chemopreventive and chemotherapeutic activities in cancer. Although phase I clinical trials have shown curcumin as a safe drug even at high doses, poor bioavailability and suboptimal pharmacokinetics largely moderated its anti-cancer activity in pre-clinical and clinical models. To improve its applicability in cancer therapy, we encapsulated curcumin in poly(lactic- co-glycolide) (PLGA) (biodegradable polymer) nanoparticles, in the presence of poly(vinyl alcohol) and poly(L-lysine) stabilizers, using a nano-precipitation technique. These curcumin nano-formulations were characterized for particle size, zeta potential, drug encapsulation, drug compatibility and drug release. Encapsulated curcumin existed in a highly dispersed state in the PLGA core of the nanoparticles and exhibited good solid-solid compatibility. An optimized curcumin nano-formulation (nano-CUR6) has demonstrated two and sixfold increases in the cellular uptake performed in cisplatin resistant A2780CP ovarian and metastatic MDA-MB-231 breast cancer cells, respectively, compared to free curcumin. In these cells, nano-CUR6 has shown an improved anti-cancer potential in cell proliferation and clonogenic assays compared to free curcumin. This effect was correlated with enhanced apoptosis induced by the nano-CUR6 formulation. Herein, we have also shown antibody conjugation compatibility of our PLGA-NP formulation. Results of this study suggest that therapeutic efficacy of curcumin may be enhanced by such PLGA nanoparticle formulations, and furthermore tumor specific targeted delivery of curcumin is made feasible by coupling of anti-cancer antibody to the NPs. © 2010 Elsevier Inc.

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