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Immunity drives TET1 regulation in cancer through NF-κB

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Science Advances  20 Jun 2018:
Vol. 4, no. 6, eaap7309
DOI: 10.1126/sciadv.aap7309
  • Fig. 1 TET1 dysregulation is associated with an altered 5hmC pattern in BLBC.

    (A) TET1 expression was assessed in RNA-seq data of the TCGA cohort (n = 851). Normal breast was compared to BC subtypes. Global comparisons between normal tissues and BC subtypes were performed by one-way analysis of variance (ANOVA). (B) Sequencing of 5hmC was performed in four pairs of matched BLBC and normal breast tissues. Paired samples were clustered on the basis of TET1 expression in the tumor (high or low; see fig. S1). The heat maps illustrate the 256 and 160 dhmRs identified in BLBC tumors with low TET1 expression (left; n = 2 matched pairs) and high TET1 expression (right; n = 2 matched pairs), respectively. 5hmC levels are expressed in counts per million (CPM). (C) Heat maps illustrating 5hmC, 5mC, and gene expression changes in BLBC with low TET1 expression (left) and high TET1 expression (right), compared to normal breast tissue (n = 2 matched pairs per group). Only coding genes associated with dhmRs are represented for each tumor group. Changes in 5mC were measured with Illumina 450K Infinium in the same matched samples in which 5hmC was sequenced. The most variant probe of the corresponding region (promoter or gene body) is represented. Expression (mRNA) changes were obtained from TCGA by comparing reads per kilobase per million mapped reads (RPKM) values of the 25 BLBC tumors showing the lowest or highest TET1 expression with those of normal breast tissue.

  • Fig. 2 High TET1 expression defines a subgroup of BLBC with low levels of immune and inflammatory markers.

    (A) TET1 expression correlates negatively with that of many genes linked to immunity, defense response, and inflammation pathways. Functional enrichment analysis was performed with DAVID on all genes whose expression showed a sufficient correlation (r > 0.25) or anticorrelation (r < −0.25) with TET1 expression based on gene expression (RPKM) in TCGA BLBC samples (n = 130). The top 5 immune categories are represented. FDR, false discovery rate. (B) Heat map illustrating expression [RNA-seq by expectation maximization (RSEM) z score] of the top 20 genes in the “immune response” category of (A) based on the correlation coefficient r. TCGA BLBC samples were ordered by TET1 expression level. (C) TET1 anticorrelates with a broad range of immune markers, according to gene expression levels in TCGA BLBC samples. The genes concerned notably include those encoding monocyte marker TYROBP, lymphocyte markers CD3D, and the NF-κB family transcription factor RELA (p65). Additional examples are shown in fig. S3A.

  • Fig. 3 High TET1 expression distinguishes BLBC tumors with low immune infiltration and a low NF-κB signal.

    (A) High TET1 expression is associated with low leukocyte infiltration in BLBC tumors. Tumor infiltration was measured by IHC. Staining for CD45, CD3, and CD20 was performed to quantify leukocytes, T lymphocytes, and B lymphocytes, respectively (n = 18). (B) Infiltration of BLBC tumors by major immune subpopulations was further analyzed by CIBERSORT, a method for characterizing the cell composition of complex tissues on the basis of their gene expression profiles (n = 130). Gene expression data (RPKM) were obtained from TCGA. (C) High TET1 expression is associated with a weak NF-κB signature in BLBC tumors (n = 130). Gene expression data (RSEM z scores) were obtained from TCGA. (D) MDA-MB-231 cells were treated with medium preconditioned by U937 myeloid cells. Transcript-level TET expression was measured by RT-qPCR (left; n = 3; data expressed as means ± SD, relative to control) (*P ≤ 0.05), and nuclear TET1 protein and p65 levels were assessed by Western blotting under control (CTL) conditions and in cells treated with conditioned medium (CM) (right).

  • Fig. 4 TET1 expression is repressed by NF-κB activation.

    (A) The gene encoding the NF-κB family member p65 was overexpressed in MDA-MB-231 cells (24 hours), and TET expression was measured by RT-qPCR (left; n = 3; data expressed as means ± SD, relative to control) (*P ≤ 0.05). Nuclear p65 levels were assessed by Western blotting (right). (B and C) NF-κB was activated in MDA-MB-231 cells by treatment with LPS [(B) 5 mg/ml] or TNF [(C) 15 ng/ml] for 4 hours. TET expression was then measured by RT-qPCR (left; n = 3; data expressed as means ± SD, relative to control) (*P ≤ 0.05; **P ≤ 0.01). Nuclear p65 levels [LPS (5 mg/ml) or TNF (15 ng/ml); 30 min] were assessed by Western blotting (right). (D) TNF-dependent activation of NF-κB in MDA-MB-231 cells was blocked by pretreating the cells with MG-132 [20 μM; 3 hours before treatment with TNF (15 ng/ml) for 4 hours]. TET expression was measured by RT-qPCR (left; n = 3; data expressed as means ± SD, relative to control). Nuclear p65 levels [20 μM; 3 hours before treatment with TNF (15 ng/ml) for 30 min] were assessed by Western blotting (right). (E) The effect of NF-κB activation was assessed in vivo in the breast in the IKMV transgenic mouse model described by Barham et al. (62). TET expression was measured by RT-qPCR (left; n = 3; data expressed as mean ± SD, relative to control) (**P ≤ 0.01), and the TET1 protein level was assessed by Western blotting (right; n = 2 controls versus 3 IKMV).

  • Fig. 5 NF-κB represses TET1 gene expression by binding to its promoter.

    (A) Schematic view of the TET1 gene promoter. Two NF-κB binding sites, named “A” and “B,” were identified. Binding site locations are indicated relative to the TET1 TSS. (B) TET1 promoter activity was assessed under NF-κB activation by cotransfecting MDA-MB-231 cells with a vector encoding firefly luciferase under the control of the TET1 promoter (TET1-LUC) and a control vector encoding Renilla luciferase (R-LUC) before treating the cells with TNF (15 ng/ml, 24 hours) or overexpressing p65 (24 hours) (n = 3, data expressed as means ± SD). Results are expressed relatively to control conditions (*P ≤ 0.05). (C) Streptavidin-agarose pulldown assays were performed to assess binding of p65 to the TET1 promoter in vitro. Pulldown of nuclear proteins extracted from MDA-MB-231 cells was achieved with biotinylated DNA probes corresponding to the TET1 promoter (TET1 prom) and with positive/negative control probes (CTL+/CTL). TNF treatment (15 ng/ml, 30 min) was used to induce nuclear translocation of p65. (D) ChIP was performed with a p65-targeting antibody or a control IgG to assess p65 binding to the TET1 promoter in MDA-MB-231 cells. TNF treatment (15 ng/ml, 30 min) was used to induce nuclear translocation of p65. NS, not significant (*P ≤ 0.05; **P ≤ 0.01). (E) Streptavidin-agarose pulldown assays were performed with biotinylated DNA probes corresponding to the predicted NF-κB binding site A or B. To assess the binding specificity, pulldowns were done with either the wild-type site or a mutated version in which the consensus NF-κB–binding sequence was disrupted (wild-type probes: A and B; mutated probes: A mut and B mut). TNF treatment (15 ng/ml, 30 min) was used to induce nuclear translocation of p65.

  • Fig. 6 TET1 and NF-κB in other cancer types.

    (A) Heat map illustrating expression (RSEM z score) of the “20–immune response gene” signature of Fig. 2B in several cancer types (from left to right: THCA SKCM, and LUAD). Data were taken from the TCGA cohort and ordered by TET1 expression in each cancer type. (B) High expression of TET1 is associated with a weak NF-κB signature in THCA (n = 509), SKCM (n = 472), and LUAD (n = 510) tumors. Gene expression data (RSEM z scores) were obtained from TCGA. (C) NF-κB was activated by treating TPC1 thyroid cancer cells, A375 melanoma cells, and A549 lung cancer cells with TNF for 4 hours. TET expression was measured by RT-qPCR (n = 3; data expressed as means ± SD, relative to control) (*P ≤ 0.05, **P ≤ 0.01, and ***P ≤ 0.001). (D) Streptavidin-agarose pulldown assays were performed as described above to assess in vitro the binding of NF-κB family member p65 to the TET1 promoter in TPC1, A375, and A549 cells [TNF (15 ng/ml), 30 min].

  • Table 1 TET1 expression correlates negatively with immune markers in many cancer types.

    The correlation between TET1 expression and the score of the “top 20 immune signature” (defined in Fig. 2) were computed for all TCGA cancer cohorts. The name of the disease and the TCGA acronym, the Pearson correlation coefficient, the associated P value, and the number of cancer samples are indicated for each cohort.

    Cancer typeTCGA cohortPearsonPNumber of samples
    Ovarian serous cystadenocarcinomaOV−0.582.1 × 10−29307
    Glioblastoma multiformeGBM−0.567.4 × 10−15166
    SarcomaSARC−0.509.6 × 10−18263
    Brain lower grade gliomaLGG−0.461.0 × 10−28530
    Uterine carcinosarcomaUCS−0.445.7 × 10−457
    Lung adenocarcinomaLUAD−0.419.0 × 10−23517
    MesotheliomaMESO−0.416.9 × 10−587
    Thyroid carcinomaTHCA−0.395.6 × 10−20509
    CholangiocarcinomaCHOL−0.382.1 × 10−236
    Uterine corpus endometrial carcinomaUCEC−0.369.1 × 10−7177
    Skin cutaneous melanomaSKCM−0.361.1 × 10−15472
    Kidney renal papillary cell carcinomaKIRP−0.334.9 × 10−9291
    Uveal melanomaUVM−0.324.0 × 10−380
    Lung squamous cell carcinomaLUSC−0.324.3 × 10−13501
    Pheochromocytoma and paragangliomaPCPG−0.312.2 × 10−5184
    Testicular germ cell tumorsTGCT−0.284.0 × 10−4156
    ThymomaTHYM−0.282.1 × 10−3120
    Adrenocortical carcinomaACC−0.252.9 × 10−279
    Prostate adenocarcinomaPRAD−0.249.6 × 10−8498
    Head and neck squamous cell carcinomaHNSC−0.183.0 × 10−5522
    Kidney chromophobeKICH−0.171.8 × 10−166
    Cervical and endocervical cancersCESC−0.132.0 × 10−2306
    Bladder urothelial carcinomaBLCA−0.097.6 × 10−2408
    Stomach adenocarcinomaSTAD−0.062.1 × 10−1415
    Kidney renal clear cell carcinomaKIRC−0.026.2 × 10−1534
    Liver hepatocellular carcinomaLIHC0.026.8 × 10−1373
    Colon adenocarcinomaCOAD0.036.8 × 10−1191
    Esophageal carcinomaESCA0.046.2 × 10−1185
    Rectum adenocarcinomaREAD0.047.1 × 10−172
    Pancreatic adenocarcinomaPAAD0.199.7 × 10−3179

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/4/6/eaap7309/DC1

    fig. S1. Characterization of BC samples used in genome-wide analyses.

    fig. S2. TET1 and immune markers in non-BLBC BC subtypes.

    fig. S3. TET1 expression and immunity in BLBC.

    fig. S4. Non-BLBC subtypes do not show a strong correlation between TET1 expression and immunity.

    fig. S5. Immune pathways modulate TET1 expression in BC.

    fig. S6. Activation of NF-κB in BC cells.

    fig. S7. NF-κB and TET1 in additional BC cell lines.

    fig. S8. Immunity and TET2 and TET3 in BLBC.

    fig. S9. TET1 promoter and streptavidin-agarose pulldown probes.

    fig. S10. TET1 and immunity in thyroid, melanoma, and lung cancers.

    fig. S11. TET1 and immunity in additional cancer types.

    fig. S12. TET1 expression and NF-κB in additional cancer types.

    table S1. List of dhmRs in BLBC (Excel file).

    table S2. Genes negatively correlating with TET1 in BLBC (TCGA)—Top 5 of gene ontology categories.

    table S3. Genes positively correlating with TET1 in BLBC (TCGA)—Top 5 of gene ontology categories.

    table S4. List of primers.

  • Supplementary Materials

    This PDF file includes:

    • fig. S1. Characterization of BC samples used in genome-wide analyses.
    • fig. S2. TET1 and immune markers in non-BLBC BC subtypes.
    • fig. S3. TET1 expression and immunity in BLBC.
    • fig. S4. Non-BLBC subtypes do not show a strong correlation between TET1 expression and immunity.
    • fig. S5. Immune pathways modulate TET1 expression in BC.
    • fig. S6. Activation of NF-κB in BC cells.
    • fig. S7. NF-κB and TET1 in additional BC cell lines.
    • fig. S8. Immunity and TET2 and TET3 in BLBC.
    • fig. S9. TET1 promoter and streptavidin-agarose pulldown probes.
    • fig. S10. TET1 and immunity in thyroid, melanoma, and lung cancers.
    • fig. S11. TET1 and immunity in additional cancer types.
    • fig. S12. TET1 expression and NF-κB in additional cancer types.
    • Legend for table S1
    • table S2. Genes negatively correlating with TET1 in BLBC (TCGA)—Top 5 of gene ontology categories.
    • table S3. Genes positively correlating with TET1 in BLBC (TCGA)—Top 5 of gene ontology categories.
    • table S4. List of primers.

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    Other Supplementary Material for this manuscript includes the following:

    • table S1. List of dhmRs in BLBC (Excel file).

    Files in this Data Supplement:

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