NOTCH1 promotes T cell leukemia-initiating activity by RUNX-mediated regulation of PKC-θ and reactive oxygen species

Abstract

Reactive oxygen species (ROS), a byproduct of cellular metabolism, damage intracellular macromolecules and, when present in excess, can promote normal hematopoietic stem cell differentiation and exhaustion1,2,3. However, mechanisms that regulate the amount of ROS in leukemia-initiating cells (LICs) and the biological role of ROS in these cells are largely unknown. We show here that the ROSlow subset of CD44+ cells in T cell acute lymphoblastic leukemia (T-ALL), a malignancy of immature T cell progenitors, is highly enriched in the most aggressive LICs and that ROS accumulation is restrained by downregulation of protein kinase C θ (PKC-θ). Notably, primary mouse T-ALLs lacking PKC-θ show improved LIC activity, whereas enforced PKC-θ expression in both mouse and human primary T-ALLs compromised LIC activity. We also show that PKC-θ is regulated by a new pathway in which NOTCH1 induces runt-related transcription factor 3 (RUNX3), RUNX3 represses RUNX1 and RUNX1 induces PKC-θ. NOTCH1, which is frequently activated by mutation in T-ALL4,5,6 and required for LIC activity in both mouse and human models7,8, thus acts to repress PKC-θ. These results reveal key functional roles for PKC-θ and ROS in T-ALL and suggest that aggressive biological behavior in vivo could be limited by therapeutic strategies that promote PKC-θ expression or activity, or the accumulation of ROS.

Main

Current therapies for T-ALL are curative in 80% of pediatric cases, but only 40% of adults with T-ALL survive beyond 5 years9. The ineffectiveness of chemotherapeutic regimens in both age groups may be attributed to an inability to target LICs10,11,12, which have increased quiescence, resistance to apoptosis and expression of DNA repair enzymes and drug efflux pumps and are localized within protective or inaccessible niches13. More efficient targeting of LICs could thus lead to marked improvements in patient outcomes.

Much recent interest has focused on the role of ROS in normal and malignant stem cell biology14. ROS are chemically reactive molecules that participate in self-propagating reactions and, if allowed to accumulate, can cause oxidative damage to intracellular macromolecules, including DNA, proteins and lipids15,16. Normal hematopoietic stem cells are uniquely sensitive to ROS1,2,3, and some cancer stem cells that have low amounts of ROS lose stem activity or become nonviable when the amounts of ROS are increased17,18.

To address the role of ROS in T-ALL, we focused first on LICs in a well-defined mouse model in which mice are reconstituted with syngeneic bone marrow cells that have been transduced with retrovirus encoding ΔE, a constitutively activated form of NOTCH1 lacking the extracellular ligand-binding domain. This approach produces aggressive, serially transplantable T cell leukemias within 8–12 weeks that are highly similar to human T-ALL19,20,21. Transplantation of primary NOTCH1-ΔE leukemia cells at a limiting dilution into secondary recipients revealed the LIC frequency to be 1 in 6,100 total cells (95% CI 1 in 2,800–13,200 cells) (Fig. 1a and Online Methods). Using the cell-permeable indicator dye dichlorodihydrofluorescein diacetate (DCFDA) to assess the amount of intracellular ROS22 in combination with various surface markers, we noted that the CD44+ fraction contained a subset of cells with low amounts of ROS (Fig. 1b). To determine whether LIC activity was asymmetrically distributed within this subpopulation, we prospectively isolated CD44+ROSlow, CD44+ROShigh and CD44 cell subsets by fluorescence-activated cell sorting (FACS) and injected them into immunocompetent syngeneic (C57BL/6) and immunocompromised nonobese diabetic severe combined immunodeficiency (NOD/SCID) Il2rg−/− (NSG) recipient mice. Notably, the CD44+ROSlow fraction showed substantially enriched LIC activity as compared to the complementary CD44+ROShigh and CD44 fractions and recapitulated the original tumor heterogeneity (Fig. 1c and Supplementary Fig. 1). Cells sorted only for CD44 expression also showed enriched LIC activity, albeit less so than CD44+ROSlow cells (Supplementary Fig. 2). We obtained similar findings in a second T-ALL model initiated by the G12D mutation of Kras19 (Fig. 1d), indicating that enriched LIC activity within the CD44+ROSlow fraction is not confined to the NOTCH1 model.

Figure 1: LICs in T-ALL are characterized by low amounts of ROS.
figure1

(a) Survival of syngenic C57BL/6 recipient mice after injection in the tail vein of various numbers of primary mouse NOTCH1-ΔE leukemia cells. (b) Flow cytometric analysis of the amount of ROS by DCFDA staining in the CD44+ and CD44 subsets and total cells from a primary mouse NOTCH1-ΔE leukemia. Data depicted are representative of at least two replicates. (c) Survival of syngenic C57BL/6 recipient mice after injection in the tail vein of primary mouse NOTCH1-ΔE leukemia cells, with the number of injected cells from each FACS-sorted subset indicated. (d) Survival of syngenic C57BL/6 recipient mice after injection in the tail vein of primary mouse leukemias harboring the G12D mutation in Kras (KrasG12D), with the number of injected cells from each FACS-sorted subset indicated. (e) Survival of NSG recipient mice after injection in the tail vein of xenograft-expanded primary human T lymphoblasts from subject M71 or D115, with the number of injected cells from each FACS-sorted subset indicated. Statistical significance in e was calculated by log-rank test. Raw survival data for all transplant experiments are summarized in Supplementary Table 1. Throughout the figure, n indicates the number of mice in each group.

To assess the relevance of these findings to human disease, we transplanted FACS-sorted ROShigh or ROSlow subsets of human T-ALL samples into NSG recipients. These samples had previously been expanded in NSG mice20 to obtain sufficient material for replicate studies. We did not include CD44 in the LIC sorting strategy because most of the xenograft-expanded human samples in our collection already contained high percentages of CD44+ cells (data not shown). Consistent with our observations in mouse models, LIC activity was enriched in the ROSlow fraction in the human leukemias (Fig. 1e). Taken together, these results show that LICs in both mouse and human T-ALL are characterized by low amounts of ROS.

PKC-θ is a crucial signaling intermediate downstream of the T cell receptor (TCR) and preTCR23,24 and is activated in T-ALLs arising in Notch3 intracellular domain (Notch3-IC) transgenic mice23. PKC-θ has also been implicated in ROS production in normal T cells25. To explore whether PKC-θ might be involved in regulating the amount of ROS in T-ALL cells, we first surveyed PKC-θ expression in the NOTCH1-ΔE mouse model. We noted that the amount of PKC-θ protein varied among the primary leukemias (Fig. 2a) and that the amounts of PKC-θ and ROS were correlated (Fig. 2b). Moreover, T-ALLs generated from PKC-θnull bone marrow24 had very low amounts of ROS, and restoration of PKC-θ expression by retroviral transduction markedly increased the amount of ROS (Fig. 2c). Of note, mature T cells from the spleens of normal PKC-θnull and wild-type mice had similar amounts of ROS (Supplementary Fig. 3), suggesting that the effects of PKC-θ are context dependent. A survey of human T-ALL cell lines and xenograft-expanded human T-ALL samples also revealed varying amounts of PKC-θ protein (Fig. 2d). Of note, retroviral PKC-θ expression in HPB-ALL cells (which have low amounts of endogenous PKC-θ) increased the amount of ROS, whereas shRNA-mediated knockdown of PKC-θ in RPMI 8402 cells (which have high amounts of endogenous PKC-θ) decreased the amount of ROS in these cells (Fig. 2e,f and Supplementary Figs. 4 and 5). Taken together, these data support a dominant role for PKC-θ in regulating the amount of ROS in both mouse and human T-ALL.

Figure 2: PKC-θ dictates the amount of ROS and is asymmetrically distributed to LIC-depleted cell fractions.
figure2

(a) Western blot analysis of PKC-θ protein expression in primary mouse NOTCH1-ΔE leukemias from wild-type (samples 1–4) and PKC-θnull (KO) backgrounds. (b,c) Flow cytometric analysis of the amounts of intracellular ROS by DCFDA staining in mouse NOTCH1-ΔE leukemias with naturally varying (PKC-θhigh and PKC-θlow) and engineered amounts of PKC-θ expression. RV-PKC-θ, PKC-θ retrovirus. (d) Western blot analysis of PKC-θ protein expression in human T-ALL cell lines and primary human T lymphoblasts after expansion as xenografts in NSG mice. The two samples for each 'M71' and 'H2718' label represent different mice engrafted with the same human sample. (e,f) Flow cytometric analysis of the amounts of intracellular ROS by DCFDA staining in human T-ALL cell lines with engineered amounts of PKC-θ expression. RV-empty, empty retrovirus control; shPKC-θ–91 and shPKC-θ–92, two different lentiviral shRNAs targeting PKC-θ; shScramble, scrambled shRNA negative control. (gj) Analysis of PKC-θ expression in FACS-sorted LIC-enriched (CD44+ and/or ROSlow) compared to LIC-depleted (CD44 or ROShigh) subsets from freshly explanted mouse NOTCH1-ΔE leukemias (g,h) and xenograft-expanded primary human T-ALLs (i,j). (g,i) Quantitative RT-PCR analysis of PKC-θ mRNA levels. Error bars indicate s.d. (h,j) Flow cytometric analysis of PKC-θ protein expression. All data depicted in this figure are representative of at least two replicates. *P < 0.05, **P < 0.01 by Student′s t test. ND, not detected.

We next asked whether the low amount of ROS that characterizes the LIC-enriched fractions might be caused by reduced PKC-θ expression. Indeed, LIC-enriched CD44+ and CD44+ROSlow fractions from mouse leukemias had significantly less PKC-θ mRNA and protein than corresponding LIC-depleted CD44 and CD44+ROShigh fractions, respectively (Fig. 2g,h and Supplementary Fig. 6a,b). Similarly, LIC-enriched ROSlow fractions of human leukemias had significantly less PKC-θ mRNA and protein than corresponding LIC-depleted ROShigh fractions (Fig. 2i,j and Supplementary Fig. 6c). These data suggest that varied expression of PKC-θ contributes to heterogeneous ROS amounts and LIC activities in subpopulations of T-ALL cells.

To address directly the role of PKC-θ in regulating LIC activity, we performed competitive transplants between PKC-θnull and wild-type leukemias, the latter of which had either high or low expression of endogenous PKC-θ. In each case, recipient mice developed leukemias within 3–4 weeks that were composed predominantly of PKC-θnull cells (Supplementary Fig. 7a). Of note, we detected a minor population of PKC-θlow cells in some recipients of PKC-θnull plus PKC-θlow cells, as might be expected if increasing PKC-θ 'dose' progressively compromised LIC activity. We also performed competitive transplants between isogenic PKC-θRV (PKC-θnull cells transduced with retroviral PKC-θ) and parental PKC-θnull cells. The recipient mice all developed leukemias within 3 weeks that were composed almost entirely of PKC-θnull cells (Fig. 3a,b), which is consistent with an antagonistic effect of enforced PKC-θ expression on LIC activity. Notably, PKC-θRV cells produced leukemia under noncompetitive transplant conditions (Fig. 3a,b), which excludes a nonspecific toxic effect of enforced PKC-θ expression. In addition, lentiviral expression of a constitutively activated form of PKC-θ26 in xenograft-expanded human T-ALL cells abrogated LIC activity (Fig. 3c and Supplementary Fig. 7b), again supporting the idea that increasing the PKC-θ dose has increasingly substantial negative effects on LIC activity.

Figure 3: Increased PKC-θ expression compromises disease reconstitution in vivo.
figure3

(a) Flow cytometric analysis of C57BL/6 recipient mice co-injected with 1 × 104 PKC-θnull (nerve growth factor receptor (NGFR)+GFP) plus 1 × 104 PKC-θRV (NGFR+GFP+) NOTCH1-ΔE leukemia cells (competitive transplant, upper arm; n = 4, recipients 1–3 depicted) or 1 × 104 PKC-θRV cells only (noncompetitive transplant, lower arm; n = 4, recipients 4–6 depicted). Data depicted are representative of two replicate experiments. Numbers in the corners of the plots indicate the percentage of total events in each quadrant. (b) Western blot analysis for PKC-θ protein expression in leukemias arising from competitive (recipients 1–3) and noncompetitive (recipients 4–6) transplant assays, as depicted in a. (c) Survival of NSG recipient mice injected with human T-ALL cells (T lymphoblasts from a xenograft-expanded human sample with very low or nondetectable amounts of endogenous PKC-θ expression (F1313-2 in Fig. 2d)) that had been transduced with lentivirus (LV) encoding a constitutively activated form of PKC-θ (A148E; PKC-θ–CA) or empty vector control (empty) and FACS sorted for the viral GFP marker. The significance P value was calculated by log-rank test. Throughout the figure, n indicates the number of mice in each group.

The frequencies of LICs in PKC-θnull and wild-type leukemias were very similar (Supplementary Fig. 8a,b), indicating that reduced PKC-θ expression is permissive to, but not sufficient for, LIC activity. Of note, PKC-θnull and wild-type leukemias showed similar latencies in both primary and secondary transplant assays (Supplementary Fig. 8a–c), and PKC-θ overexpression or knockdown did not affect cell proliferation (Supplementary Fig. 8d,e), arguing against the possibility that leukemias with lower expression of PKC-θ prevail in vivo simply as a result of differential rates of proliferation. Rather, these data support the idea that PKC-θ has a dominant role in determining the ability of T-ALL cells to reconstitute or 'initiate' disease in vivo. Of note, T-ALL cells with reduced PKC-θ expression or activity showed resistance to chemotherapy and radiation in vitro (Supplementary Fig. 9), suggesting that low PKC-θ expression or activity might contribute to poor outcome in patients undergoing standard therapy.

To explore how PKC-θ expression is regulated in T-ALL, we examined available microarray data and discovered that the transcription factor RUNX1, which was recently described as a tumor suppressor in T-ALL27,28,29, was highly correlated with PKC-θ expression in four separate patient cohorts totaling 264 primary samples30,31,32,33 (Fig. 4a and Supplementary Fig. 10). Chromatin immunoprecipitation sequencing (ChIP-Seq) for RUNX1 in the NOTCH1-mutated human T-ALL cell line CUTLL1 revealed four high-confidence RUNX1 binding sites within the PKC-θ locus, one of which was located at the proximal promoter (associated with histone H3 trimethyl Lys4 (H3K4me3) chromatin marks) and three of which were within putative intronic enhancers (associated with H3K4me1 chromatin marks)34 (Fig. 4b), suggesting that RUNX1 might regulate PKC-θ expression. Consistent with this idea, shRNA-mediated knockdown of RUNX1 resulted in decreased amounts of PKC-θ mRNA and protein (Fig. 4c,d). Given that RUNX3 has been reported to repress RUNX1 in some contexts35, we found it notable that ChIP-Seq in CUTLL1 cells36 revealed two high-confidence NOTCH1 and CBF1/RBPJ-suppressor of hairless-Lag1 (CSL) binding sites located 30–60 kb upstream of the RUNX3 P1 promoter with associated H3K4me1 chromatin marks (Fig. 4e). This suggested that NOTCH1 might regulate RUNX3 expression, and thus we hypothesized that a transcriptional circuit might be active in T-ALL cells in which NOTCH1 activates RUNX3, RUNX3 represses RUNX1 and RUNX1 activates PKC-θ (Fig. 4f). In fact, RUNX3 overexpression or knockdown resulted in reciprocal changes in RUNX1 expression, whereas blocking NOTCH by treating cells with γ-secretase inhibitor (GSI) decreased the expression of RUNX3 and increased the expression of RUNX1 and PKC-θ (Fig. 4g,h and Supplementary Fig. 11a–d). Dominant-negative mastermind-like 1 (DN-MAML)37 recapitulated the effects of GSI on RUNX3, confirming that these effects are specific to NOTCH signaling (Supplementary Fig. 11e,f). Furthermore, GSI treatment caused the amounts of ROS to increase, a response that did not occur in PKC-θnull mouse leukemias and was abrogated by PKC-θ inhibition or RUNX1 knockdown in human T-ALL cells (Fig. 4i and Supplementary Fig. 12). Despite these effects, PKC-θnull leukemia cells remained sensitive to GSI-induced growth arrest in vitro6,20,37 (Supplementary Fig. 13). These results reveal a previously unknown mechanism connecting NOTCH1 to LIC activity though negative regulation of PKC-θ expression, thus resulting in reduced amounts of intracellular ROS, and are consistent with prior studies showing that NOTCH1 promotes LIC activity7,8. Of note, we also observed NOTCH1 to contribute to regulation of CD44 expression (Supplementary Fig. 14), further supporting its role in defining LICs. Variation among individual cell lines suggests that other factors probably impinge on components of the NOTCH1–RUNX3–RUNX1–PKC-θ transcriptional circuit; however, the overall consistent effects support the relevance of these results. Prior studies have identified mouse T-ALL LICs to be enriched in either the c-KitmidCD3+ fraction (VEC-Cre/PTENnull model)38 or the CD4CD8 (double negative or DN) fraction (SIL-SCL/Lck-LMO1 model)39. In the NOTCH1-ΔE model used here, we found LICs to be enriched in the CD44+ROSlow fraction but to show variable expression of CD4 and CD8 (Supplementary Fig. 15). Further studies will be needed to determine to what extent these LIC-containing populations overlap and how different oncogenes affect LIC identity.

Figure 4: NOTCH1 represses PKC-θ and ROS through RUNX3 and RUNX1.
figure4

(a) Microarray expression profile data from primary human T-ALL samples (GSE26713). Samples are ordered from left to right by PKC-θ expression. The top 20 genes most correlated with PKC-θ are ordered from top to bottom. Identified transcription factors are indicated, with their Pearson correlation coefficient (r) in parentheses. Expression values are normalized for each probeset across all samples with a mean of 0 and an s.d. of 1. (b) ChIP-Seq reads for the indicated antibodies over the human PKC-θ locus from the human T-ALL cell line CUTLL1. Promoters (green arrows) and putative enhancers (red arrows) are indicated. (c) Quantitative RT-PCR analysis of PKC-θ mRNA levels in human T-ALL cell lines (CUTLL1 and KOPTK1) transduced with lentiviral shRNAs against RUNX1 or scrambled negative control (shScramble). Error bars indicate the s.d. for assays performed in triplicate. **P < 0.01, ***P < 0.001 by Student′s t test. (d) Western blot analyses of PKC-θ and RUNX1 protein amounts in CUTLL1 cells after knockdown of RUNX1 using two different shRNAs (shRUNX1-58 and shRUNX1-59). Numbers below the blot indicate the fold change after normalization to the loading control, β-actin. (e) ChIP-Seq reads for the indicated antibodies over the human RUNX3 locus from the human T-ALL cell line CUTLL1. Promoters (green arrows) and putative enhancers (red arrows) are indicated. (f) Schematic of the transcriptional circuit involving NOTCH1, RUNX3, RUNX1 and PKC-θ. (g,h) Western blot analyses of RUNX1, RUNX3 and PKC-θ protein amounts in CUTLL1 cells after lentiviral overexpression of RUNX3 (LV-RUNX3; g) and NOTCH inhibition with GSI (1 μM compound E; h). Numbers below each blot indicate the fold change after normalization to the loading control, β-actin. (i) Flow cytometric analysis of the amounts of intracellular ROS by DCFDA staining in T-ALL cells treated with GSI (3 d), myristoylated PKC-θ pseudosubstrate inhibitor (added 24 h before assay) and/or transduced with RUNX1 shRNAs. Gated live events are shown. Data depicted are representative of at least two replicates.

Our findings suggest that PKC-θ may have a broad role in regulating LIC activity in T-ALL. Although the identified pathway linking NOTCH1 and PKC-θ is probably most relevant in tumors with activating NOTCH1 (ref. 6) or inactivating F-box and WD-40 domain protein 7 (FBW7)4,5 mutations, PKC-θ expression may be similarly reduced in tumors with loss-of-function RUNX1 mutations (recently reported to occur in 4–18% of T-ALLs27,28,29) or elevated expression of RUNX3 or by mechanisms that are independent of NOTCH1 and RUNX. Alternatively, cell signaling events that modulate PKC-θ activity rather than expression per se40 may also have important effects on LIC activity. Further studies will be required to explore the intriguing possibility that therapies that promote PKC-θ expression, activity or both may antagonize LICs and thereby improve clinical outcomes in patients with T-ALL.

Methods

Mice.

PKC-θ (Prkcq) knockout mice (backcrossed over ten generations to C57BL/6) have been described previously24. We obtained C57BL/6 (Ly5.2), B6.SJL-PtprcaPepcb/BoyJ (Ly5.1) and NSG mice from in-house colonies maintained at the British Columbia Cancer Agency (BCCA) Animal Resource Centre. We housed all mice in specific pathogen–free facilities according to institutional guidelines. All breeding and animal experiments were performed under protocols approved by the University of British Columbia (UBC) Animal Care Committee and according to guidelines of the Canadian Council on Animal Care.

Viruses.

We produced high-titer, replication-defective retroviral supernatants by transient transfection of PlatE cells41 and produced lentivirus by transient cotransfection of 293T cells with packaging and envelope vectors, as previously described42. Murine stem cell virus (MSCV)-based retroviral expression vectors encoding constitutively active NOTCH1 (ΔE or L1601P-ΔPEST alleles) with internal ribosomal entry site (IRES)-GFP or IRES–truncated NGFR (tNGFR) cassettes for tagging of transduced cells have been described19,21,37. We constructed similar retroviral expression vectors carrying wild-type PKC-θ complementary DNA (cDNA). The DN-MAML retroviral construct encoding amino acids 13–74 of human MAML1 fused to GFP has been previously described37. We expressed RUNX3 and constitutively activated PKC-θ (with the A148E mutation)26 cDNAs from the lentiviral vector pRRL-cPPT/CTS-MNDU3-PGK-GFP-WPRE, which is composed of the pRRLsin-18 backbone43,44, central polypurine tract (cPPT) with central DNA flap45,46, modified myeloproliferative sarcoma virus long terminal repeat U3 region (MNDU3) promoter47,48, phosphoglycerate kinase (PGK)-GFP marker and woodchuck hepatitis virus post-transcriptional regulatory element (WPRE) (plasmid construction details available on request). We cloned the RNAi Consortium (TRC) shRNAs49 targeting PKC-θ (shPKC-θ–91, TRCN0000001791; shPKC-θ–92, TRCN0000001792), RUNX1 (shRUNX1-58, TRCN0000013658; shRUNX1-59, TRCN0000013659) and RUNX3 (shRUNX3, TRCN0000235674) into the pLKO.1puro lentivector, as previously described50. We obtained the scrambled shRNA control (shScramble) in pLKO.1puro vector from Addgene (1864)51. We verified all constructs by sequencing. We isolated virally transduced cells by FACS or by selection with puromycin, as applicable.

Bone marrow transplantation.

To generate primary mouse leukemias, we transduced bone marrow cells from 5-fluorouracil–treated mice (C57BL/6 background) with retrovirus by spinoculation20. Three days later, we injected 10,000–40,000 GFP+ or NGFR+ cells (including at least 1 × 105 normal bone marrow cells) into the tail veins of lethally irradiated (810 rad) C57BL/6 recipients. For serial transplantation experiments, we injected varying numbers of total or FACS-sorted primary leukemia cells by tail vein into nonirradiated C57BL/6 or sublethally irradiated (200 rad) NSG secondary recipient mice. We monitored all transplant recipient mice daily for clinical signs of leukemia. We also followed the leukemia engraftment and progression in some recipients with periodic peripheral blood sampling and flow cytometric analysis.

Human samples.

We obtained all human samples with appropriate institutional approvals (UBC/BCCA Research Ethics Board, Institutional Review Board of the Institut Universitaire d'Hématologie/Université Paris Diderot, Karmanos Cancer Center Institutional Review Board and MD Anderson Cancer Center Institutional Review Board) and informed consent under guidelines established by the Declaration of Helsinki. We isolated mononuclear cells from fresh bone marrow aspirate or peripheral blood samples by density gradient centrifugation and used them directly or cryopreserved them. Subsequent analyses used human-specific antibodies against CD45 (1:20, HI30), CD3 (1:20, OKT3), CD4 (1:20, OKT4), CD8 (1:20, RPA-T8) and/or CD44 (1:100, IM7) (eBioscience) to discern human T-ALL lymphoblasts.

Cell culture.

All established cell lines have been reported previously6,52,53. We cultured these cell lines in RPMI 1640 medium supplemented with 10% FCS, 1 mM sodium pyruvate, 2 mM L-glutamine and antibiotics. We isolated primary mouse leukemia cells from the bone marrow or spleen of moribund mice and, where indicated, cultured them briefly in vitro in complete media as described above with the supplemental cytokines interleukin-2 (IL-2) and IL-7, each at 10 ng ml−1 (Peprotech). We expanded primary human T-ALL lymphoblasts as xenografts in sublethally irradiated NSG mice and, where indicated, cultured them briefly in vitro on MS5/MS5-DL1 feeders7 or immobilized Ig-DL1 ligand54, as previously described20.

To inhibit PKC-θ enzymatic activity, we treated cells in vitro with 5 μM myristoylated PKC-θ pseudosubstrate inhibitor (539636, Calbiochem). To inhibit Notch signaling, we treated cells in vitro with 1 μM GSI XXI (compound E; ALX-270-415, Alexis). To reduce the amounts of ROS directly, we treated cells in vitro with the vitamin E-derivative antioxidant, Trolox (Calbiochem), at 50 μM final concentration.

We achieved doxycycline-inducible expression of DN-MAML37 by lentiviral transduction of cells with pLVX-Tet-On Advanced (Clontech, CMV-IE promoter replaced with EF1-α promoter) followed by selection in G418 and then with DN-MAML in pLVX-Tight-Puro (Clontech) followed by selection in puromycin. Cells were treated with 500 ng ml−1 doxycycline for 4 d prior to assay.

Chemotherapy and radiation resistance assays.

To assess drug sensitivity in vitro, we plated cells at 7.5 × 105 cells ml−1 per well in 24-well dishes, treated them with doxorubicin (5 μg ml−1 for primary mouse leukemias or 2 μg ml−1 for human cell lines) or dexamethasone (10 μg ml−1 for primary mouse leukemias or 100 μg ml−1 for human cell lines) and then assayed them 48–72 h later. To assess radiation sensitivity in vitro, we plated cells at 7.5 × 105 cells ml−1 per well in 24-well dishes, treated them with X-irradiation using a single 10-Gy dose and then assayed them 48–72 h later. We measured cell viability in each case by flow cytometry for exclusion of propidium iodide. To assess DNA damage in vitro, we plated cells at 7.5 × 105 cells ml−1 per well in 24-well dishes, treated them with X-irradiation using a single 1-Gy dose and then analyzed them for phosphorylated histone H2A.X by flow cytometry 1 h later.

Flow cytometry.

We stained mouse leukemia cells with fluorochrome or biotin-conjugated antibodies against CD45.1 (1:100, A20), CD45.2 (1:100, 104), CD3 (1:100, 145-C11), CD4 (1:100, GK1.5 or RM4-5), CD8 (1:100, 53-6.7) and CD44 (1:100, IM7) (eBioscience, Biolegend). We used antibodies to human CD271 (1:50, 130-091, Miltenyi Biotec) to detect the retroviral NGFR marker. We performed intracellular staining with antibodies to PKC-θ (1:5, 560216, BD Biosciences), RUNX3 (1:40, MAB3765, R&D Systems) and phosphorylated histone H2A.X (Ser139) (1:50, 9718, Cell Signaling) after paraformaldehyde fixation and permeabilization with 90% ice-cold methanol (for PKC-θ and H2A.X) or saponin (for RUNX3), as specified by the manufacturer. Where applicable, we also used fluorochrome-conjugated secondary antibodies (1:100 dilution, Biolegend). To assess ROS concentrations, we stained live cells with 5-(and-6)-carboxy-2′,7′-DCFDA (carboxy-H2-DCFDA), dihydroethidine (DHE) or Mitosox, according to the manufacturer's instructions (Invitrogen). We measured cell proliferation by BrdU incorporation according to the manufacturer's instructions (BrdU kit, BD Biosciences). We measured cell viability by propidium iodide exclusion. We performed FACS analysis and sorting on FACS Calibur, Canto2, Vantage DiVa and Aria2 cytometers (BD Biosciences). We analyzed flow cytometry data using FlowJo software (TreeStar).

Quantitative RT-PCR.

We extracted total RNA after cell lysis in TRIzol reagent (Invitrogen). We generated first-strand cDNA by reverse transcription with SuperScript III (Invitrogen) using a mix of random 15-mer and anchored oligo(dT) primers and then amplified the product by real-time PCR using Platinum SYBR Green qPCR SuperMix-UDG (Invitrogen) and a Bio-Rad Chromo4 optical detector. Specific primer sequences are available on request. We assayed each sample in triplicate and calculated expressions by the ΔΔCt method with normalization to β-actin.

Western blot and immunofluorescence.

To generate whole-cell lysates, we washed cells in ice-cold PBS and then lysed them in ice-cold 50 mM Tris-HCl (pH 7.4), 1% Nonidet P-40, 0.25% sodium deoxycholate, 150 mM sodium chloride, 1 mM sodium orthovanadate, 1 mM sodium fluoride, 2.5 mM sodium pyrophosphate, 1 mM EDTA, 1 mM phenylmethylsulfonyl fluoride and protease inhibitor cocktail (1:500, 539134, Calbiochem). We ran whole-cell lysates on SDS-PAGE gels and then transferred them to Hybond ECL membranes (Amersham). We blocked membranes with 5% nonfat dry milk and then probed them with primary antibodies to PKC-θ (1:500, 2059, Cell Signaling), RUNX1 (1:1,000, 39000, Active Motif), RUNX3 (1:1,000, MAB3765, R&D), mitogen-activated protein kinase 1 (ERK2) (1:1,000, sc-154, Santa Cruz), β-actin (1:6,000, A1978, Sigma) and tubulin (1:5,000, MAB3408, Chemicon). We used horseradish peroxidase–conjugated secondary antibodies (1:5,000–1:10,000, Jackson ImmunoLaboratories) with ECL western blotting substrate (32106, Pierce) and detected signals by autoradiography. We quantified band intensities using ImageJ software55.

We performed immunofluorescence on formaldehyde-fixed, methanol-permeabilized cells from cytospin preparations using PKC-θ primary antibody (1:25, 2059, Cell Signaling) followed by AlexaFluor 488–conjugated goat anti-rabbit secondary antibody (1:100, A-11008, Invitrogen) and DAPI counterstaining. We acquired images using a Zeiss Axioplan fluorescence microscope with 20× and 40× objectives.

ChIP-Seq.

We performed ChIP with the ChIP Assay kit (Millipore). Briefly, we treated cells with 1% formaldehyde for 10 min at 37 °C, lysed them in 1% SDS, 10 mM EDTA and 50mM Tris (pH 8.1) and sonicated them to obtain DNA fragments ranging in length from 200 bp to 600 bp. We then immunoprecipitated chromatin with antibodies to the following: RUNX1 (1:2,000, ab23980, Abcam), NOTCH1 (amino acids 2,278–2,470) (1:2,000)56, CSL (1:1,000, kind gift of E. Kieff), H3K4me1 (1:2,000, ab8895, Abcam), H3K4me3 (1:2,000, 07-745, Millipore) and H3K27me3 (1:1,000, 07-449, Millipore). After overnight incubation with antisera at 4 °C, we captured immunoprecipitated chromatin with Protein A agarose beads, which we subsequently washed, and eluted the bound chromatin. After reversal of crosslinks, we purified DNA using the QIAquick PCR purification kit (Qiagen). We prepared ChIP-Seq libraries according to the Illumina ChIP DNA library preparation kit. After the addition of adaptors, we amplified libraries by 18 cycles of PCR, size selected (150–250 bp) them by electrophoresis and purified them using a Qiagen gel extraction kit. After quality control testing on an Agilent 2100 Bioanalyzer, we subjected the library to deep sequencing using an Illumina Genome Analyzer II in the Harvard Medical School Biopolymers Core facility. We aligned sequencing reads to human genome build hg19 and analyzed them using CisGenome57. The number of mapped reads ranged from 1 × 107 to 3.4 × 107 per library.

Microarray data analysis.

We downloaded normalized datasets from the Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/) and analyzed them using dChip software58.

Statistics.

We analyzed quantitative data using GraphPad Prism 5 software. We calculated LIC frequencies from limiting dilution transplant results, as previously described59.

Accession codes

Accessions

Gene Expression Omnibus

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Acknowledgements

We would like to thank Z. Sun (City of Hope, Duarte, California) for providing PKC-θ knockout mice, J. Fletcher and W. Ou (Brigham and Women's Hospital, Boston, Massachusetts) for PKC-θ shRNA lentivectors, E. Kieff (Brigham and Women's Hospital, Boston, Massachusetts) for CSL antibody, I. Bernstein (Fred Hutchinson Cancer Research Center, Seattle, Washington) for Ig-DL1 ligand, F. Pflumio (Commissariat à l'Énergie Atomique Fontenay-aux-Roses, France) for the MS5-DL1 cell line and E. Martignani for help with immunofluorescence. We would also like to thank P. Ballerini (Hôpital Armand Trousseau, Paris, France), T. Leblanc (Hôpital Saint-Louis, Paris, France), L. Matherly (Karmanos Cancer Institute, Detroit, Michigan) and M.J. You (MD Anderson Cancer Center, Houston, Texas) for providing patient T-ALL samples. This work was supported by grants from the Canadian Institutes of Health Research/Terry Fox Foundation, the Leukemia and Lymphoma Society of Canada, the Cancer Research Society, the Lymphoma Foundation Canada (to A.P.W.) and the US National Cancer Institute (P01CA119070 to J.C.A.). M.Y.C. was supported by a career development award from the US National Cancer Institute (K08CA120544). A.P.W. was a Michael Smith Foundation for Health Research Scholar.

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V.G. and A.P.W. designed the experiments. V.G., C.R.J., S.H.L., O.O.S., O.N., C.W. and S.G. generated the data. V.G. and A.P.W. interpreted the results. M.Y.C. provided reagents and advice. H.W. and J.C.A. generated and analyzed ChIP-Seq data. R.K.H. and C.E. provided advice and discussion. V.G. and A.P.W. wrote the paper.

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Correspondence to Andrew P Weng.

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Giambra, V., Jenkins, C., Wang, H. et al. NOTCH1 promotes T cell leukemia-initiating activity by RUNX-mediated regulation of PKC-θ and reactive oxygen species. Nat Med 18, 1693–1698 (2012). https://doi.org/10.1038/nm.2960

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