Application of B-cell receptor (BCR) pathway inhibitor ibrutinib for chronic lymphocytic leukemia (CLL) is a major breakthrough, yet the downstream effects following inhibition of BCR signaling and during relapse await further clarification. By comparative phosphoproteomic profiling of B cells from patients with CLL and healthy donors, as well as CLL B cells collected at multiple time points during the course of ibrutinib treatment, we provided the landscape of dysregulated phosphoproteome in CLL and its dynamic alterations associated with ibrutinib treatment. Particularly, differential phosphorylation events associated with several signaling pathways, including BCR pathway, were enriched in patient CLL cells. A constitutively elevated phosphorylation level of KAP1 at serine 473 (S473) was found in the majority of CLL samples prior to treatment. Further verification showed that BCR activation promoted KAP1 S473 phosphorylation, whereas ibrutinib treatment abolished it. Depletion of KAP1 in primary CLL cells decelerated cell-cycle progression and ectopic expression of a KAP1 S473 phospho-mimicking mutant accelerated G2–M cell-cycle transition of CLL cells. Moreover, temporal phosphoproteomic profiles using a series of CLL cells isolated from one patient during the ibrutinib treatment revealed the dynamic changes of several molecules associated with BCR signaling in the ibrutinib responsive and recurrent stages.

Implications:

This phosphoproteomic analysis and functional validation illuminated the phosphorylation of KAP1 at S473 as an important downstream BCR signaling event and a potential indicator for the success of ibrutinib treatment in CLL.

B-cell chronic lymphocytic leukemia (CLL), the most common adult leukemia in the Western populations, is a low-grade B-cell lymphoid malignancy characterized by the presence of monoclonal leukemic B cells in the peripheral blood and infiltration into the lymph nodes and bone marrow (1). Although its course is usually indolent, a substantial subset of patients with CLL ultimately need active therapy. Previously, cytotoxic chemotherapy agents and anti-CD20 mAbs formed the backbone of treatments (2–5). However, only a few of these chemo-immunotherapy regimens provide modest overall survival benefits while leading to initial clinical responses (4, 6). Thus, new therapeutic modalities are necessary for this unmet medical need.

In the past decade, novel targeted therapies, such as B-cell receptor (BCR) signaling inhibitors, have demonstrated drastic therapeutic efficacy for CLL (7–9). Once BCR encounters an antigen, it induces cross-linking of the BCR complex, which ignites a signaling transduction cascade that is essential for B-cell proliferation and activation (10). BCR signaling is reportedly important for the establishment and maintenance of CLL (11), and BCR signaling inhibitors, such as ibrutinib (targeting to BTK) and idelalisib (targeting to PI3K), showed impressive therapeutic results, leading to approvals by regulatory authorities in many countries worldwide (12, 13). It appears that the addiction of CLL cells to BCR signaling is not triggered by driver mutations, but rather a functional addiction (13). Downstream signaling cascades of the BCR pathway are complicated; particularly, the molecular insight into the relationship between BCR signaling-targeted therapy and CLL progression remains to be elucidated. Thus, to clarify key mechanisms of action of BCR signaling inhibitors, signaling pathway alterations occurring further downstream of BCR inhibitor treatment are of interest. To address this issue, we conducted quantitative phosphoproteomics experiments to compare the phosphoproteome of healthy donor B cells, CLL B cells from treatment-naive patients, as well as the CLL cells from patients during their time course of ibrutinib therapy. The phosphoproteomics landscape and further verification revealed the significance of KAP1 S473 phosphorylation in CLL.

Collection of human CLL specimens, human B-cell culture, and cell lines

The research project was conducted in accordance with recognized ethical guidelines (Declaration of Helsinki) and approved by institutional review boards (IRB) of both National Taiwan University Hospital (NTUH; Taipei, Taiwan; Research Ethics Committee A, 201907037RINA) and Academia Sinica (Taipei, Taiwan; IRB on Biomedical Science Research, AS-IRB-BM-19043). The written informed consent was obtained from each patient before sample collections. B cells were isolated from peripheral blood of healthy donors and patients with CLL (obtained from Taipei Blood Center and NTUH, respectively). The methods for the detection of IGHV somatic hypermutation status and the analysis of nucleotide sequences, which were aligned to the IMGT/V-QUEST database, were previously described (14). The isolation of human B cells followed the methods of Ficoll density gradient centrifugation and protocols of CD19+ magnetic beads purification (Miltenyi Biotec; ref. 15). CLL cell lines including Mec1 (RRID: CVCL_1870), JVM-2 (RRID: CVCL_1319), JVM-3 (RRID: CVCL_1320), JVM-13 (RRID: CVCL_1318) were purchased from DSMZ (Leibniz, Germany) and were passaged for experiments within 3 months after thawing. These obtained CLL cell lines have been tested for authentication by exome sequence and RNA sequencing (RNA-seq). All the CLL cells were cultured in RPMI1640 medium (Life Technologies) containing 10% FBS, 100 U/mL penicillin, 100 μg/mL streptomycin (Life Technologies), and 50 μmol/L 2-mercaptoethanol at 37°C with 5% CO2. All the cell lines used in this study are free from Mycoplasma contamination as examined by EZ-PCR Mycoplasma test kit (Biological Industries, 20–700–20). For B-cell stimulation, human B cells and cell lines were seeded at 2 × 106 cells/mL and stimulated with goat–anti-human IgM F(ab')2 (10 μg/mL, Jackson ImmunoResearch Laboratories). In some experiments, CLL cells isolated from patients were cocultured with a feeder cell line, the puromycin-resistant L4.5 cells (L4.5puro), which were developed from the L929 cell line (Thermo Fisher Scientific) expressing human CD40 L as well as a puromycin resistant gene (16). For coculture experiments, L4.5puro cells were seeded at 2 × 104 cells/mL. After overnight incubation, L4.5puro cells were treated with mitomycin-C (10 μg/mL, Sigma-Aldrich) for 3 hours at 37°C. Then primary CLL cells at 2 × 106 cells/mL were seeded on washed L4.5puro cells, followed by stimulation with CpG ODN 2006 (1.5 μg/mL, InvivoGen) and transduction with lentiviral vectors. In some experiments, BTK inhibitor ibrutinib (10 μmol/L, Cayman), JNK inhibitor SP600125 (20 μmol/L, Selleckchem), Chk1 inhibitor LY2603218 (20 nmol/L, Selleckchem), Chk2 inhibitor PV1019 (1 μmol/L, Calbiochem), PKC inhibitor Gö6983 (30 nmol/L, Selleckchem) or Doxorubicin (1 μg/mL, Cayman) were used to treat CLL cells.

Lentiviral and short hairpin RNA transduction

A cDNA encoding full-length hKAP1 was cloned by RT-PCR from normal human peripheral blood B cells and then subcloned into pFUGW lentiviral expression vector (16). The procedure for performing PCR based site-directed mutagenesis of KAP1 expression plasmid to generate KAP1 S473A, S473E mutant will be available upon request. Lentiviral vectors carrying shKAP1 or vector control used to knockdown human KAP1 were obtained from National RNAi core Facility (Academia Sinica). Short hairpin RNA (shRNA) sequence against KAP1 was 5′- CCTGGCTCTGTTCTCTGTCCT-3′ (KAP1-1) and 5′-CTCTGTTCTCTGTCCTGTCAC-3′ (KAP1-2), and control shRNA sequence targeting to luciferase was 5′-CTTCGAAATGTCCGTTCGGTT-3′. The production of the lentiviral vector was as described (17). Multiplicity of infection (MOI) of 1 to 5 in the presence of 5 μg/mL polybrene (Sigma-Aldrich) was used for lentiviral transduction. In shKAP1 and control vector transduced CLL cell lines and primary CLL cells, puromycin (1 μg/mL, Sigma-Aldrich) was added to select transduced cells at 72 hours and 24 hours, respectively, after transduction.

Protein purification and immunoblotting

Protein extraction and immunoblotting were performed as described (17). Briefly, human primary B cells or CLL cell line cells were lysed in lysis buffer containing 50 mmol/L Tris-HCl (pH8.0), 150 mmol/L NaCl, 5 mmol/L EDTA, 0.5% Triton X-100, 0.1% sodium deoxycholate, protease and phosphatase inhibitors (Roche), and incubated on ice for 30 minutes. Protein extracts were then collected by centrifugation at 13,523 g at 4°C for 15 minutes. Antibodies used in immunoblotting are: anti-KAP1 Ser473 (Abcam, ab133225, 1:1000; Biolegend, catalog no. 654102, 1:1000), anti-KAP1 (Abcam, ab22553, 1:3000), anti- BTK Tyr223 (Cell Signaling Technology, #5082, 1:1000), anti-BTK (Cell Signaling Technology, #8547, 1:1000), anti-Cyclin A2 (GeneTex, GTX103042, 1:500), anti-Cyclin B1 (GeneTex, GTX100911, 1:500), anti-Cdc2 (GeneTex, GTX108120, 1:500), anti-Cdc25a (GeneTex, GTX102308, 1:500), anti-WEE1 (Cell Signaling Technology, #13084, 1:1000), anti-tubulin (Thermo Fisher Scientific, 14-4502-82, 1:2000), anti-rH2AX antibody (Cell Signaling Technology, #9718), horseradish peroxidase (HRP)-conjugated anti-actin antibody (GeneScript, A00730), and HRP-conjugated anti-Flag antibody (Sigma-Aldrich, A8592). Secondary antibodies used in the study were goat anti-mouse IgG HRP-conjugated antibody (Sigma-Aldrich, A2554, 1:5000) and goat anti-rabbit IgG HRP-conjugated antibody (Sigma-Aldrich, A0545, 1:5000). The immunoreactive proteins were detected by Western Bright Sirius chemiluminescent detection reagent (Advansta, R-030027-C50) as described previously (17). We used iBright FL1000 (Thermo Fisher Scientific) to capture and quantify the immunoreactive protein band, and ensured that protein band intensity was within the linear range. In most cases, the band intensity of phosphorylated KAP1 at S473 was compared with the band intensity of total KAP1 in the same lane.

Flow cytometry, cell proliferation, and cell cycle analysis

The procedures for performing flow cytometric analysis were as described (17). The antibodies used in the study are: anti-human CD5 (clone: UCHT2; BD PharMingen) conjugated with FITC and anti-human CD19 (clone: H1B19; BD PharMingen) conjugated with PE. Cell proliferation was assessed by using CellVue dye conjugated with allophycocyanin (APC; 1 μmol/L; Thermo Fisher Scientific) according to the manufacturer's protocol. Cell viability was determined by trypan blue (Thermo Fisher Scientific, 10282) staining or propidium iodide (PI; Biotinum, 40048, 1:100) staining. The fluorescence-labeled cells were analyzed using a BD FACSCanto II (Becton Dickinson). To perform cell cycle analysis, 1 × 106 Mec1 or JVM-3 cells were washed by PBS and reseeded in medium containing Hoechst 33342 (3 μg/mL, Thermo Fisher Scientific) for 1.5 hours in 37°C incubator, followed by analysis with BD FACSAria (Becton Dickinson) with UV laser. For analyzing the proliferation of CLL cells from patients, CLL cells were washed off from L4.5puro feeder cells after 3 or 5 days in coculture and fixed by fixation/permeabilization solution (BD PharMingen). DNA components were stained with PI (50 μg/mL, Sigma-Aldrich) for 30 minutes at 37°C. In some experiments, Mec1 cells at G2–M stage were sorted by cell sorter based on the Hoechst 33342 staining distribution.

Functional and network analysis

Ingenuity Pathway Analysis (IPA) software (IPA, QIAGEN Inc.; https://www.qiagenbioinformatics.com/products/ingenuitypathway-analysis) was used for enrichment of functional terms from differentially phosphorylated proteins. The Benjamini–Hochberg multiple test correction was used with other options at default setting. Informatic analysis of the Protein–Protein Interaction (PPI) annotation was performed using the STRING database (18). The STRING database defines PPI based on confidence ranges for data scores (high >0.7; medium >0.4; low >0.15; ref. 18). In this study, we selected a confidence score of more than 0.4 to construct our PPI network and visualization was performed by Cytoscape version 3.8.2 (19).

Statistical analysis

Statistical analyses were performed by two-tailed unpaired t tests and P < 0.05 was considered statistically significant. All experimental data shown in this study are presented by the mean ±SEM obtained from at least three biological replicates.

All other detailed methods for RNA isolation and qRT-PCR, phosphoproteomics analysis were provided in the Supplementary Information

Phosphoproteomic landscape and quantitative alteration of CLL B cells

To establish global phosphoproteomic profiles of normal and CLL B cells in the discovery phase, peripheral B cells (CD19+) were first isolated from 6 treatment-naïve patients and 3 healthy donors (see individual characteristics in Supplementary Table S1). Personalized quantitative phosphoproteomic analyses were performed for each individual sample to compare the CLL and healthy groups by a label-free quantitation strategy (Supplementary Fig. S1A; ref. 17). Quantitative analysis of individual samples (Supplementary Data S1; Supplementary Fig. S1B) revealed 290 differentially expressed phosphopeptides (192 phosphoproteins) between 6 patients and 3 healthy donors, of which upregulation of 198 phosphopeptides and downregulation of 86 phosphopeptides were observed in CLL B cells compared with healthy controls (P < 0.05, Mann–Whitney U test). Hierarchical clustering analysis demonstrated that the phosphoproteomic profiles of CLL samples were distinguished from those of healthy donors (Fig. 1A). These altered phosphoproteins are classified in many functional categories, including large groups of transcription regulators, enzymes, and kinases, as well as one growth factor (hepatoma-derived growth factor) and two phosphatases (CD45 and INPP5F; Supplementary Fig. S1C). It was reported that B cells from patients with CLL showed constitutive phosphorylation of signal transducer and activator of transcription 1 (STAT1) on S727 (20). This site-specific phosphorylation event was also observed with a higher level in 5 patients with CLL compared with the control samples (P < 0.05; Fig. 1B; Supplementary Fig. S1D).

Figure 1.

Summary of quantitative phosphoproteomic analysis of CLL samples. A, Heatmap of differentially regulated phosphopeptides between 6 patients with CLL and 3 healthy donors as determined by label-free quantitation strategy (P < 0.05). B, Volcano plot showing the distribution of the relative abundances of phosphopeptides in B cells of patients with CLL and controls. Differentially expressed phosphopeptides were determined by Mann–Whitney U test (P < 0.05) and highlighted with color. Red and green dots represent phosphopeptides that were more and less abundant in patient cells, respectively. C, Molecular functions of the 192 altered phosphoproteins classified by IPA database. D, PPI network of differentially expressed phosphoproteins was grouped into three k-mean clusters as suggested by STRING v11 software and visualized by Cytoscape v 3.8.2. The differential phosphorylated levels are indicated via node color (red for upregulation and green for downregulation). E, Prediction of candidate upstream regulators of 21 proteins with novel differentially phosphosites by qPhos and IPA database. Proteins with novel phosphorylation sites found in B-cell–related signaling pathways were labeled within the green shade.

Figure 1.

Summary of quantitative phosphoproteomic analysis of CLL samples. A, Heatmap of differentially regulated phosphopeptides between 6 patients with CLL and 3 healthy donors as determined by label-free quantitation strategy (P < 0.05). B, Volcano plot showing the distribution of the relative abundances of phosphopeptides in B cells of patients with CLL and controls. Differentially expressed phosphopeptides were determined by Mann–Whitney U test (P < 0.05) and highlighted with color. Red and green dots represent phosphopeptides that were more and less abundant in patient cells, respectively. C, Molecular functions of the 192 altered phosphoproteins classified by IPA database. D, PPI network of differentially expressed phosphoproteins was grouped into three k-mean clusters as suggested by STRING v11 software and visualized by Cytoscape v 3.8.2. The differential phosphorylated levels are indicated via node color (red for upregulation and green for downregulation). E, Prediction of candidate upstream regulators of 21 proteins with novel differentially phosphosites by qPhos and IPA database. Proteins with novel phosphorylation sites found in B-cell–related signaling pathways were labeled within the green shade.

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Pathway analysis of these 192 differentially phosphorylated proteins revealed the significantly enriched pathways in CLL B cells (P < 0.05; Supplementary Table S2). Among them, BCR signaling is the second highest-ranked pathway along with many BCR-related signaling pathways, such as ERK/MAPK signaling and PI3K signaling (Supplementary Table S2). Interestingly, systemic lupus erythematosus (SLE) signaling, which is well documented to be closely associated with autoimmune diseases and lymphoproliferative disorders (21, 22), was ranked as the top pathway. We also found that SLE and BCR signaling pathways shared similar pathway components, including PTPRC, CD22, NFATC2, and NFATC1. Enrichment of molecular and cellular functions of these differential phosphoproteins were performed utilizing IPA, which implicated the majority of proteins with differential phosphorylation levels in CLL B cells are associated with “RNA posttranscriptional modification” (n = 27, P = 5.12E-15), “gene expression” (n = 64, P = 2E-9), “cellular death and survival” (n = 14, P = 1.44E-8), “cellular development” (n = 49, P = 3.38E-06), and “cellular growth and proliferation” (n = 47, P = 3.38E-06; Fig. 1C).

Based on the literature that the establishment of CLL is correlated with dysregulated cell proliferation and apoptosis (23, 24), we specifically focused on the dysregulated phosphoproteins functionally linked to “cellular death and survival” and “cellular growth and proliferation”. To gain further mechanistic and functional insights of the proteins of interest, we used a network-based analysis against the STRING v11 database (18). The PPI network was thus grouped and annotated in three clusters, including “adaptive immune system and lymphocyte proliferation” (18 phosphoproteins), “chromatin regulator” (17 phosphoproteins), and “regulation of leukemia transcription and translation” (6 phosphoproteins; Fig. 1D; Supplementary Data S2), which may imply their functions related to CLL leukemogenesis.

Among the 3,736 phosphosites, interestingly, 962 novel phosphosites had not been previously reported (Supplementary Data S1), as compared with the UniProt database (https://www.uniprot.org) which includes the most comprehensive PhosphoSitePlus resource for protein phosphorylation in human. Based on the annotation by IPA, 176 proteins of 258 novel phosphosites were relevant in either canonical B-cell–related pathways or B-cell lymphoma (Supplementary Data 1). For example, phosphorylated CD19 (S499), NFATC1 (S153, S359), and NFATC2 (S761, S765) were identified, but had not been previously reported. Among these novel sites, notably, 115 sites were only identified in the patients, such as FOXO1 (T333) and NFATC2 (S761) that are present in the majority of patients. Compared with previous phosphoproteomic study of immune cells (25), these previously unreported site-specific phosphorylation events suggest unique characteristics of primary B cells and patient-derived CLL cells. Based on qPhos database, a resource composed of experimentally derived phosphoproteome dataset (26), we were able to annotate the putative upstream regulators for 21 proteins with differentially phosphorylated novel sites (Fig. 1E; Supplementary Data S3). In particular, six proteins with novel phosphorylation sites found in CLL, including CD19, CD22, HLA-A, INPP5F, NFATC1, and NFATC2, are annotated in canonical B-cell–related pathways by IPA.

BCR signaling is a dominant pathway in CLL. Our data revealed the differential site-specific phosphorylation of many protein components in the BCR signaling pathway, such as CD22, CD19, CD45, and NFAT (Fig 2, see complete pathway in Supplementary Fig. S2). The SYK downstream phosphorylation was downregulated in CLL, suggesting an inhibitory effect of the SYK/14-3-3 module on CLL progression, while canonical BCR downstream signaling through CARD11/TAK1/NF-κB was activated in patients. In addition, 6 patients exhibited downregulation of PKCβ T642 phosphorylation, which is known to negatively regulate BCR-mediated Ca2+ signaling through reduced membrane recruitment and subsequent activation of BTK (27), suggesting a potential role in promoting BCR activation. Among BCR signaling molecules related to proliferation and apoptosis, levels of KAP1 S473 phosphorylation were observed to be higher in 5 patients, with an average of 5.9-fold change compared with controls. Comparing the quantitative phosphoproteomic results with global downstream KAP1 targets that are annotated in the IPA (https://www.qiagenbioinformatics.com/products/ingenuitypathway-analysis), we identified four targets (CXCR4, RRP1B, MLL5, and HDAC1) that are differentially expressed in the patients with CLL (Supplementary Data 1). Among them, HDAC1 is annotated to interact with KAP1 by STRING database (18). KAP1, encoded by TRIM28 (28), has been shown to interact with STAT1 and function as a transcriptional regulator of IFN/STAT1-mediated signaling (29). Though the STAT1 phosphorylation at S727 shows a slightly significant elevation in patients with CLL (Supplementary Fig. S1D), whether the KAP1 phosphorylation at S473 is linked with the STAT1 S727 phosphorylation in CLL pathogenesis remains to be investigated.

Figure 2.

Schematic representation of identified proteins and their phosphorylation sites in BCR signaling. Phosphorylation sites are colored in red or green to indicate increased or decreased phosphorylation in patient CLL cells compared with controls, respectively, as well as their fold change. Annotation for the involvement in cell proliferation or apoptosis is shown as blue or orange filling, respectively, inside the circle representing each protein. The red star or green star indicated the differential phosphorylation sites present in CLL cells compared with CD5+ B cells from healthy donors.

Figure 2.

Schematic representation of identified proteins and their phosphorylation sites in BCR signaling. Phosphorylation sites are colored in red or green to indicate increased or decreased phosphorylation in patient CLL cells compared with controls, respectively, as well as their fold change. Annotation for the involvement in cell proliferation or apoptosis is shown as blue or orange filling, respectively, inside the circle representing each protein. The red star or green star indicated the differential phosphorylation sites present in CLL cells compared with CD5+ B cells from healthy donors.

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Given that the majority of CLL cells from patients are CD5+, which only represent a small fraction of peripheral B cells in healthy donors (30), we next used enriched CD5+ B cells from both healthy donors and patients for quantitative phosphoproteomics analysis. An independent phosphoproteomics study was then conducted to quantitatively compare the phosphoproteomic profiles of CD5+ B cells in patients and healthy donors, and to validate the differential phosphoproteins in CD5+ B cells of patients (Supplementary Fig. S3). Our results consistently showed that the level of KAP1 S473 phosphorylation in CLL cells from patients is 1.9-fold higher than that in enriched CD5+ B cells from healthy donors (Fig. 2; Supplementary Data S4). Taken together, our results suggest that constitutive phosphorylation of KAP1 at S473 site may be associated with CLL pathogenesis downstream of BCR signaling.

KAP1 S473 phosphorylation is regulated by BCR signaling

It is worth noting that KAP1 is critical for B-cell development. Genetic ablation of KAP1 specifically in B cells of mice resulted in developmental defects at the mature B stage (28). In addition to the essential role of KAP1 in normal B cells, KAP1 S473 phosphorylation has been demonstrated to be important in various cancer cells, especially osteosarcoma, adenocarcinoma cells, and retinal pigment epithelium cells challenged with DNA damage-inducing agents (31, 32). These reports highlight the potential significance of KAP1 S473 phosphorylation in CLL formation, and prompted us to hypothesize that S473 phosphorylation of KAP1 may play a role in CLL pathogenesis. To validate the enhancement of KAP1 S473 phosphorylation in CLL cells of patients, immunoblotting was used to verify phosphoproteomic results. Compared with the two healthy donors, different degrees of elevated KAP1 S473 phosphorylation were observed in peripheral blood B-cell samples from all 4 patients (Fig. 3A).

Figure 3.

KAP1 S473 phosphorylation is regulated by BCR signaling. A, Immunoblotting showing the levels of KAP1 S473 phosphorylation and total KAP1 in CD19+ B cells isolated from peripheral blood of four patients with CLL and two healthy donors. Immunoblotting showing the levels of KAP1 S473 phosphorylation and total KAP1 after anti-human IgM (25 μg/mL) treatment of peripheral B cells from a healthy donor (B) and a patient with CLL (C). D, Immunoblotting showing the levels of KAP1 S473 phosphorylation and KAP1 protein at different time points after anti-human IgM stimulation (25 μg/mL) of multiple CLL cell lines. E, Immunoblotting showing the levels of phosphorylation of BTK in Mec1 and JVM-3 CLL cell lines after ibrutinib treatment. F, Immunoblotting showing the levels of phosphorylation of KAP1 in Mec1 and JVM-3 CLL cell lines after ibrutinib treatment. G, Immunoblotting showing the levels of indicated proteins at different time points in anti-IgM (25 μg/mL) stimulated CLL cells from patients in the absence or presence of ibrutinib (10 μmol/L) treatment. H, Immunoblotting showing the levels of KAP1 S473 phosphorylation and KAP1 protein in Mec1 CLL cells after treatment with the indicated inhibitors at the following concentration: ibrutinib (10 μmol/L), JNK inhibitor (SP600126, 20 μmol/L), Chk1 inhibitor (LY260318, 20 nmol/L), Chk2 inhibitor (DV1019, 1 μmol/L), and PKC inhibitor (Gö6983, 30 nmol/L). The ratio of phosphorylated KAP1 at S473 to total KAP1, as well as the ratio of phosphorylated BTK to total BTK in each line of blots in A,B,C,D,F,G, and H were indicated. Actin served as the protein loading control and was not used for the calculation of the ratio of KAP1 phosphorylation. H, healthy donors.

Figure 3.

KAP1 S473 phosphorylation is regulated by BCR signaling. A, Immunoblotting showing the levels of KAP1 S473 phosphorylation and total KAP1 in CD19+ B cells isolated from peripheral blood of four patients with CLL and two healthy donors. Immunoblotting showing the levels of KAP1 S473 phosphorylation and total KAP1 after anti-human IgM (25 μg/mL) treatment of peripheral B cells from a healthy donor (B) and a patient with CLL (C). D, Immunoblotting showing the levels of KAP1 S473 phosphorylation and KAP1 protein at different time points after anti-human IgM stimulation (25 μg/mL) of multiple CLL cell lines. E, Immunoblotting showing the levels of phosphorylation of BTK in Mec1 and JVM-3 CLL cell lines after ibrutinib treatment. F, Immunoblotting showing the levels of phosphorylation of KAP1 in Mec1 and JVM-3 CLL cell lines after ibrutinib treatment. G, Immunoblotting showing the levels of indicated proteins at different time points in anti-IgM (25 μg/mL) stimulated CLL cells from patients in the absence or presence of ibrutinib (10 μmol/L) treatment. H, Immunoblotting showing the levels of KAP1 S473 phosphorylation and KAP1 protein in Mec1 CLL cells after treatment with the indicated inhibitors at the following concentration: ibrutinib (10 μmol/L), JNK inhibitor (SP600126, 20 μmol/L), Chk1 inhibitor (LY260318, 20 nmol/L), Chk2 inhibitor (DV1019, 1 μmol/L), and PKC inhibitor (Gö6983, 30 nmol/L). The ratio of phosphorylated KAP1 at S473 to total KAP1, as well as the ratio of phosphorylated BTK to total BTK in each line of blots in A,B,C,D,F,G, and H were indicated. Actin served as the protein loading control and was not used for the calculation of the ratio of KAP1 phosphorylation. H, healthy donors.

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Given that BCR signaling is essential for CLL formation, and KAP1 S473 phosphorylation is induced by T-cell receptor stimulation (33), we wondered whether KAP1 S473 phosphorylation can be enhanced by BCR cross-linking. In peripheral blood B cells from both healthy donors and patients with CLL, the phosphorylation level of KAP1 S473 was prominently elevated upon ligation of BCR with anti-IgM (Fig. 3B and C). Consistently, multiple CLL cell lines, including Mec1, JVM-2, JVM-3, and JVM-13, showed increased levels of KAP1 S473 phosphorylation after anti-IgM cross-linking (Fig. 3D). We next examined potential mechanisms by which KAP1 S473 phosphorylation is elevated in BCR signaling. First, we examined if ibrutinib, a kinase inhibitor targeting BTK in BCR signaling, affects KAP1 S473 phosphorylation. Treatment with ibrutinib not only blocked BTK phosphorylation (Fig. 3E), but also significantly reduced KAP1 S473 phosphorylation in tested CLL cell lines (Fig. 3F). The effect of ibrutinib on blocking KAP1 S473 phosphorylation was also found in anti-IgM stimulated CLL cells from patients (Fig. 3G). To further investigate the signaling cascade that induces KAP1 S473 phosphorylation, two inhibitors targeting kinases in BCR signaling pathways, JNK and protein kinase C (PKC), as well as an inhibitor of Chk1/2 previously reported to phosphorylate KAP1 at S473 in retinal pigment epithelium cells (32), were tested in the Mec1 and JVM-3 cell lines. The results showed that the treatment with JNK inhibitor SP600125 caused the most significant reduction of the level of KAP1 S473 phosphorylation, without changing KAP1 expression (Fig. 3H; Supplementary Fig. S4A). Other inhibitors also partially inhibited KAP1 S473 phosphorylation, suggesting that it is induced by BCR ligation, and can be regulated by BTK and its downstream JNK signaling cascade.

KAP1 knockdown and ibrutinib treatment affect cell proliferation, and S473 phosphorylation facilitates G2–M cell-cycle progression

As KAP1 S473 phosphorylation is regulated by BTK, we wondered whether the effect of ibrutinib treatment on the inhibition of CLL proliferation relies on the attenuation of KAP1 S473 phosphorylation. To answer this question, we first tested the effect of ibrutinib on proliferation and cell viability of CLL cell lines. We found that cell proliferation, as determined by dilution of CellVue dye, was decreased after treatment of Mec1 and JVM-3 CLL cells with ibrutinib compared with solvent control (Fig. 4A). Although ibrutinib treatment caused slightly elevated levels of cell death, it did not significantly affect CLL cell viability after statistical analysis (Supplementary Fig. S5A). Therefore, we suspected that ibrutinib-induced deceleration of cell proliferation may be causally linked to the attenuated KAP1 S473 phosphorylation. To further test this hypothesis, we compared the cell proliferation and cycle distribution of KAP1-knockdown (shKAP1) and control knockdown (vector) CLL cells. The results shown in Fig. 4B confirmed the knockdown efficiency of two independent lentiviral vectors coexpressing shRNA against KAP1 and a puromycin resistant gene. The expression of the puromycin resistant gene allowed the selection of KAP1 shRNA expressing CLL cells by puromycin. We also established a feeder cell line coexpressing CD40 L and a puromycin-resistant gene (L4.5puro cells). The L4.5puro feeder cells are resistant to puromycin selection due to the expression of the puromycin resistant gene. It is noted that peripheral B cells from patients with CLL showed delayed cell-cycle progression into S phase after KAP1 knockdown and CpG stimulation in a coculture system with L4.5puro cells in the presence of puromycin (Fig. 4C). Consistent with the previous notion that primary CLL cells are arrested in the G0–G1 stage of cell cycle (34), we found that the majority of CLL cells were in the G0–G1 stage before cocultured with feeder cells (day 0; Fig. 4C). A reduced fraction of CpG-stimulated primary CLL cells proceeded into the S phase on both day 3 and day 5 in the coculture after depletion of KAP1, as compared with those cells transduced with vector control. Similarly, primary CLL suspension culture derived from another patient showed reduced cell division after knockdown of KAP1 (Supplementary Fig. S6). These results suggest that KAP1 regulates cell proliferation in CLL cells. We thus went on to test the effect of KAP1 knockdown on the cell-cycle distribution of Mec1 cells. We found that knockdown of KAP1 in Mec1 cells led to cell-cycle arrest at G2–M stage (Fig. 4D). Given that KAP1 S473 phosphorylation has been shown to affect the G2–M checkpoint (35), we further examined the expression of known targets of KAP1, CDC2, and CDC25A (36) as well as other genes involved in the regulation of G2–M transition, including WEE1, CCNA2, and CCNB1 (37), in control and KAP1 knockdown Mec1 cells. We found an increased mRNA level of WEE1, CDC2, and CDC25A in sorted KAP1 knockdown Mec1 cells at G2–M stage as compared with that in sorted control knockdown Mec1 cells at G2–M stage (Fig. 4E), suggesting an involvement of epigenetic reprogramming of KAP1 targets in CLL cells. However, at the protein levels, we only observed that WEE1 level is elevated in KAP1 knockdown Mec1 cells (Fig. 4F). Consistently, in another CLL cell line, JVM-3, after KAP1 knockdown (Supplementary Fig. S4B), we found the G2–M accumulation (Supplementary Fig. S4C), reduced cell proliferation (Supplementary Fig. S4D) and elevated WEE1 protein level (Supplementary Fig. S4E). We thus suspected that G2–M accumulation after KAP1 knockdown may at least partly be attributed to the increased expression of WEE1 as WEE1 is a gatekeeper of G2 arrest (38). However, we found that KAP1 may not affect cell viability of CLL cell lines, because knockdown of KAP1 did not substantially affect cell death of Mec1 or JVM-3 cells (Supplementary Fig. S5B).

Figure 4.

KAP1 S473 phosphorylation promotes cell-cycle progression of CLL cells. A, Cell proliferation, as determined by CellVue dye dilution, of Mec1 and JVM-3 CLL cell lines following indicated treatments. B, Immunoblotting showing the knockdown of KAP1 expression in Mec1 cells by two independent shKAP1s. C, Schematic flowchart of coculture of primary CLL cells with L4.5puro feeder cells. CLL cells were transduced with a lentiviral vector carrying a puromycin-resistant gene either plus shRNA against KAP1 or not. Cell-cycle distribution, including cells in the apoptotic and dead phase (A/D), was determined by PI staining at days 0, 3, and 5. D, Hoechst 33342 staining showing the cell-cycle distribution of vector-transduced or KAP1- knockdown Mec1 cells. E, Knockdown of KAP1 caused increased mRNA levels of WEE1, CDC2, and CDC25A in Mec1 cells. qRT-PCR showing the relative levels of indicated mRNA in the sorted G2–M stage of KAP1-knockdown and control knockdown Mec1 cells. F, Immunoblotting showing that knockdown of KAP1 in Mec1 cells caused increased WEE1 protein levels. G, Expression of exogenous Flag- tagged WT KAP1 and KAP1(S473E) in vector-transduced or KAP1-knockdown Mec1 cells. H, Hoechst 33342 staining showing cell-cycle distribution of cells described in G. I, Statistics analysis of the result in H. J, Immunoblotting showing the equal levels of exogenous WT KAP1, KAP1-S473A, and KAP1-S473E in Mec1 cells. K, Cell proliferation analysis of WT KAP1, KAP1-S473A, and KAP1-S473E in vector control-transduced or KAP1-knockdown Mec1 cells. Results in the right panel of D and I are mean ± SEM (n = 3). Actin served as the internal control in B,F,G, and J. *, P < 0.05, **, P < 0.01, and ***P < 0.001. D0, day 0; D1, day 1; D2, day 2; D3; day 3; D5, day 5.

Figure 4.

KAP1 S473 phosphorylation promotes cell-cycle progression of CLL cells. A, Cell proliferation, as determined by CellVue dye dilution, of Mec1 and JVM-3 CLL cell lines following indicated treatments. B, Immunoblotting showing the knockdown of KAP1 expression in Mec1 cells by two independent shKAP1s. C, Schematic flowchart of coculture of primary CLL cells with L4.5puro feeder cells. CLL cells were transduced with a lentiviral vector carrying a puromycin-resistant gene either plus shRNA against KAP1 or not. Cell-cycle distribution, including cells in the apoptotic and dead phase (A/D), was determined by PI staining at days 0, 3, and 5. D, Hoechst 33342 staining showing the cell-cycle distribution of vector-transduced or KAP1- knockdown Mec1 cells. E, Knockdown of KAP1 caused increased mRNA levels of WEE1, CDC2, and CDC25A in Mec1 cells. qRT-PCR showing the relative levels of indicated mRNA in the sorted G2–M stage of KAP1-knockdown and control knockdown Mec1 cells. F, Immunoblotting showing that knockdown of KAP1 in Mec1 cells caused increased WEE1 protein levels. G, Expression of exogenous Flag- tagged WT KAP1 and KAP1(S473E) in vector-transduced or KAP1-knockdown Mec1 cells. H, Hoechst 33342 staining showing cell-cycle distribution of cells described in G. I, Statistics analysis of the result in H. J, Immunoblotting showing the equal levels of exogenous WT KAP1, KAP1-S473A, and KAP1-S473E in Mec1 cells. K, Cell proliferation analysis of WT KAP1, KAP1-S473A, and KAP1-S473E in vector control-transduced or KAP1-knockdown Mec1 cells. Results in the right panel of D and I are mean ± SEM (n = 3). Actin served as the internal control in B,F,G, and J. *, P < 0.05, **, P < 0.01, and ***P < 0.001. D0, day 0; D1, day 1; D2, day 2; D3; day 3; D5, day 5.

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To further elucidate the effect of KAP1 S473 phosphorylation on CLL cell proliferation and cell-cycle progression, we generated a KAP1 S473 phosphosite-mimicking mutant, in which S473 is replaced by glutamic acid (S473E). Similar expression levels of exogenous Flag-tagged wild-type (WT) KAP1 and KAP1(S473E) were observed in Mec1 cells (Fig. 4G). Cell-cycle distribution of WT KAP1- and KAP1 (S473E)-overexpressing Mec1 cells were analyzed, with or without knockdown of endogenous KAP1. We found that expression of KAP1-S473E reduced the frequency of cells staying in the G2–M phase (Fig. 4H and I). A phosphorylation-dead form of S473 (S473A) was generated and used for CellVue dilution analysis again (Fig. 4J). Consistently, we found that, as compared with Mec1 cells expressing WT-KAP1, those expressing KAP1-S473E showed enhanced CellVue dilution, while those expressing KAP1-S473A had reduced cell proliferation (Fig. 4K). Therefore, our data suggest that phosphorylation of KAP1 at S473 is linked with the increased cell proliferation and G2–M cell cycle progression.

Clinical correlations of KAP1 S473 phosphorylation

We further collected peripheral blood B cells from healthy donors and patients with CLL, and performed immunoblotting to examine their KAP1 S473 phosphorylation levels (Supplementary Table S1 and Supplementary Fig. S7). To examine whether levels of KAP1 S473 phosphorylation correlate with the initial clinical status of patients, we extracted the results of treatment-naïve patients (n = 22) for exploration. KAP1 S473 phosphorylation levels in patients were significantly higher than those in peripheral blood B cells from healthy donors (Fig. 5A). Besides, a significantly positive association was observed between CLL disease stages and KAP1 S473 phosphorylation (Fig. 5A). The KAP1 S473 phosphorylation had significantly elevated levels and increased trend in patients at Binet Stage A and B compared with that from healthy donors analyzed by two-tailed unpaired t tests (P < 0.01 and P < 0.05 respectively). Although patients at Binet stage C had a trend of increased KAP1 S473 phosphorylation levels compared with patients at stages A and B, its statistical significance requires further study due to the limited number of patients with Binet C recruited in this study (Fig. 5A). In addition, we collected serial samples from 2 patients with relapsed/refractory CLL during their courses of salvage ibrutinib treatment. The S473 phosphorylation level of KAP1, computed after normalization to the total KAP1 expression from the same patient, was reduced during the early period of ibrutinib treatment (patient X at 5 weeks after treatment and patient Y at 8 weeks after treatment; Fig. 5B). This trend positively correlated with the dramatically decreased numbers of peripheral CD5+ B cells in patients who were documented as responsive to the treatment (Fig. 5C). Interestingly, it was noted that the KAP1 S473 phosphorylation level prominently increased prior to the clinical relapse of patients after ibrutinib therapy. For patient X, KAP1 S473 phosphorylation started to rise at 8 weeks, while relapse occurred at 20 weeks with the recurrence presented as rapidly progressive lymphocytosis and lymphadenopathy; the same trend was also observed for patient Y, who relapsed at 35 weeks with the recurrence presented as progressive lymphadenopathy.

Figure 5.

Phosphorylation profiles of KAP1 S473 and phosphoproteomic alteration in B cells from patients receiving ibrutinib treatment. A, Correlation of KAP1 S473 phosphorylation level and Binet stage of patients with CLL. Results (mean ± SEM) were analyzed by two-tailed unpaired t tests (*, P < 0.05 and **, P < 0.01). Samples from 22 patients with CLL who had not received prior therapeutics were used for analysis. All ratios of protein band intensity of KAP1 S473 phosphorylation/total KAP1 were normalized to that of CLL#1. B, Immunoblotting of KAP1 S473 phosphorylation and total KAP1 in CD19+ B cells isolated from the peripheral blood of two patients at different time points after ibrutinib treatment. The protein band intensity of KAP1 S473 phosphorylation/total KAP1 was indicated. C, Changes in the numbers of CD5+ B cells in peripheral blood of ibrutinib-treated patients. D, Clustering of differentially expressed phosphorylation sites identified from the CLL cells of patient X treated with ibrutinib for 3, 5, 8, 12, and 20 weeks. The quantities of phosphopeptides were normalized to those before the ibrutinib treatment. NS, not significant. wks, weeks.

Figure 5.

Phosphorylation profiles of KAP1 S473 and phosphoproteomic alteration in B cells from patients receiving ibrutinib treatment. A, Correlation of KAP1 S473 phosphorylation level and Binet stage of patients with CLL. Results (mean ± SEM) were analyzed by two-tailed unpaired t tests (*, P < 0.05 and **, P < 0.01). Samples from 22 patients with CLL who had not received prior therapeutics were used for analysis. All ratios of protein band intensity of KAP1 S473 phosphorylation/total KAP1 were normalized to that of CLL#1. B, Immunoblotting of KAP1 S473 phosphorylation and total KAP1 in CD19+ B cells isolated from the peripheral blood of two patients at different time points after ibrutinib treatment. The protein band intensity of KAP1 S473 phosphorylation/total KAP1 was indicated. C, Changes in the numbers of CD5+ B cells in peripheral blood of ibrutinib-treated patients. D, Clustering of differentially expressed phosphorylation sites identified from the CLL cells of patient X treated with ibrutinib for 3, 5, 8, 12, and 20 weeks. The quantities of phosphopeptides were normalized to those before the ibrutinib treatment. NS, not significant. wks, weeks.

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To further reveal the role of KAP1 S473 phosphorylation in CLL signaling pathways in response to ibrutinib, phosphoproteomic profiles of the peripheral blood B cells isolated from patient X, who developed earlier relapse/refractory CLL, before and after ibrutinib treatment for 3, 5, 8, 12, and 20 weeks were subjected to quantitative phosphoproteomic analysis using an isobaric tandem mass tags (TMT) labeling method (Supplementary Fig. S8). Peripheral blood B cells at different time points were subjected to cell lysis, isobaric labeling, and phosphopeptide enrichment by immobilized metal affinity chromatography (IMAC), followed by LC-MS/MS analysis. The proteomic profiling was also performed from the unbound peptides to evaluate the alteration either at protein expression or phosphorylation degree. A total of 2,697 proteins and 5,412 phosphopeptides from 2,003 phosphoproteins were identified and quantified (Supplementary Data S5). During the course of treatment, the ratio of quantification result of KAP1 S473 phosphorylation to total level KAP1 shows KAP1 S473 phosphorylation was inhibited after 5 weeks and then significantly elevated at the end of the treatment; the patient had disease progression and soon passed away 20 weeks after starting ibrutinib treatment. These results indicate that KAP1 S473 phosphorylation level may be associated with the onset of relapse, suggesting its potential utility as an indicator of relapse after ibrutinib treatment (Fig. 5D). In addition, based on clustering analysis, ibrutinib treatment induced higher phosphorylation levels of SYK (S297/Y296), CD45 (S975), and PKCβ (T642) in the BCR signaling pathway at the beginning of treatment, but not in the 20th week when CLL reoccurred. Another group of phosphosites, including NF-κB (T943), MEK2 (S23), and NCF2 (S213), were inhibited immediately after ibrutinib treatment, but showed elevated expression at the twentieth week. These phosphorylation events not only revealed potential protein panels for monitoring disease recurrence but also identified possible drug targets. Taken together, KAP1 S473 phosphorylation might serve as a potential companion biomarker for early detection of the development of resistance to ibrutinib or other BCR pathway inhibitors.

Targeting various kinases in BCR signaling has demonstrated efficacy for treating CLL (7–9). However, the efficacy of such treatments varies, likely because these kinases participate in other signaling pathways and the clinical effects stem from simultaneous inhibition of multiple signaling responses. Our study established a comprehensive database for personalized phosphoproteomic atlases of cancerous and normal B cells from patients with CLL and healthy donors. Previous literatures only documented a few phosphorylation sites from patients with CLL and most were BCR-responsive tyrosine residues, such as Lyn (Y397; ref. 39) Syk (Y352), BLNK (Y84), and Cbl (Y700/Y774; ref. 40). Although only approximately 1% of the total phosphorylation sites that we observed were on tyrosine residues owing to their very low abundance, the identified serine/threonine phosphorylation events comprise novel phosphosites complementary to the currently known CLL signaling pathway. Our quantitative phosphoproteomics results identified several novel phosphorylation sites associated with BCR signaling as well as the perturbed signaling events that were not normally present in B cells from healthy donors (Supplementary Data S1). Thus, data from our phosphoproteomic analyses provide additional knowledge of the BCR signalosome, as well as other signaling pathways in CLL. Peripheral blood B cells contain around 10% CD5+ B cells and the expression of CD5 promotes B-cell survival (30). It is noted that comparative phosphoproteomics between enriched CD5+ B cells from healthy donors and patients with CLL also revealed several elevated phosphorylation sites in CLL cells, including HSP90AA1 (S263), VIM (S56), RBM15 (S294), and KAP1 (S473). The potential utility of KAP1 as a companion biomarker for the recurrence of CLL serves as an example of the potential clinical value of differentially expressed phosphoproteomic signatures in CLL.

Here, our phosphoproteomics study revealed that KAP1 S473 phosphorylation is prominently elevated in CLL samples and correlated with the severity of disease progression. However, status of the IGHV mutation of treatment-naïve CLL samples seemed to not be associated with levels of KAP1 S473 phosphorylation (Supplementary Table S1). Although KAP1 is known as a corepressor that controls the expression of multiple genes (41), a role for KAP1 in the activation of gene expression has also been reported (42, 43). KAP1 function is highly regulated by phosphorylation in response to many cellular events (44, 45). Phosphorylation of KAP1 on S473 decreases its interaction with the critical heterochromatin component, HP1, resulting in the derepression of cell cycle genes including CCNA2, CDC2, and CDC25A (36). Given that primary CLL cells are arrested in the cell cycle (34), we could only claim that KAP1 affects CLL cell proliferation induced by CpG treatment. While in Mec1 cells, we found that KAP1 may regulate G2–M cell-cycle transition through repressing the expression of WEE1. Notably, although PKC-δ has previously been reported as the kinase responsible for KAP1 S473 phosphorylation, our results also showed a partial blockage of S473 phosphorylation of KAP1 by a PKC-δ inhibitor. KAP1 S473 phosphorylation has also been shown to be regulated by ATM-Chk1/2 signaling during DNA damage responses (32, 46). Similarly, partial inhibition of KAP1 S473 phosphorylation by Chk1 and Chk2 inhibitors was observed in CLL cells. We here found that knockdown of KAP1 in Mec1 cells caused G2–M cell-cycle accumulation, while overexpression of S473E KAP1 accelerated the G2–M progression. It is plausible that one of the mechanisms by which elevated KAP1 S473 phosphorylation contributes to CLL pathogenesis is the G2–M checkpoint defect, which may allow damaged/mutated cells to enter mitosis, resulting in increased genomic instability and a risk of CLL progression (47).

It is well known that CLL is much less prevalent in Asia, a fact which makes clinical sample collection for clinical verification much more difficult in the current study (48). However, KAP1 S473 phosphorylation in primary CLL samples can still be shown significantly higher than normal B cells. In addition, in patients with Binet C disease, despite the limited number of available samples to be recruited in this study, there is a trend that KAP1 S473 phosphorylation level is elevated. This finding further suggests the role of KAP1 S473 phosphorylation in both pathogenesis and disease evolution in CLL. The identification of BTK/PLCG2 mutations in patients relapsed after ibrutinib therapy suggests that reactivation of BTK pathway downstream signals is an important mechanism of BTK inhibitor therapy failure (49). The early recurrence of elevated KAP1 S473 phosphorylation before frank disease relapse in the two ibrutinib-treated patients is in line with our hypothesis that phosphorylation of KAP1 at S473 is an important downstream signaling process of BTK pathway that may drive the proliferation of CLL cells. Thus, KAP1 S473 phosphorylation might also be a potential biomarker for early identification of future resistance to BTK inhibitor therapy. A previous study demonstrated that ibrutinib treatment does not induce DNA damage (50). In this study, we find that ibrutinib treatment inhibits KAP1 Ser473 phosphorylation. It has been reported that KAP1 is phosphorylated at Ser473 in response to DNA damage (46). We think constitutive KAP1 Ser473 phosphorylation in CLL cells is not associated with the status of DNA damage in CLL cells, as overexpression of S473E or S473A form of KAP1 did not change the expression γH2AX, the DNA damage marker, in Mec1 cells (Supplementary Fig. S9A). Further, ibrutinib treatment in Mec1 cells did not influence γH2AX levels, despite that KAP1 S473 phosphorylation level is blocked in the presence of ibrutinib, and that positive control doxorubicin treatment causes induction of γH2AX levels and KAP1 S473 phosphorylation (Supplementary Fig. S9B). Altogether, our results are consistent with the previous report that ibrutinib treatment does not induce DNA damage (50). In conclusion, our findings not only portray the first phosphoproteomic atlas and their alteration in response to ibrutinib therapy of patients with CLL, but also identify KAP1 S473 phosphorylation as an important downstream molecular event of BTK signaling pathway that links with the pathogenesis of CLL with a potential utility of clinical applications.

No disclosures were reported.

J.-L. Wu: Data curation, formal analysis, validation, investigation, visualization, methodology, writing–original draft. H.-Y. Wu: Data curation, formal analysis, validation, investigation, visualization, methodology, writing–original draft. S.-J. Wu: Data curation, formal analysis, validation, investigation, visualization, methodology, writing–original draft. H.-Y. Tsai: Formal analysis, validation. S.-H. Weng: Formal analysis, validation. K.-T. Lin: Software, formal analysis. L.-I. Lin: Formal analysis, methodology. C.-Y. Yao: Formal analysis, methodology. M. Zamanova: Formal analysis, methodology. Y.-Y. Lee: Software, formal analysis. T. Angata: Conceptualization, resources. H.-F. Tien: Conceptualization, resources. Y.-J. Chen: Conceptualization, resources, supervision, investigation, project administration, writing–review and editing. K.-I Lin: Conceptualization, resources, supervision, investigation, project administration, writing–review and editing.

This work was supported by the Academia Sinica (grant no. AS-TP-108-ML06) and Ministry of Science and Technology (MOST; grant no. 109-2320-B-001-023-MY3 to K.-I. Lin and grant no. 110-2811-M-001-531-MY3 to Y.-J Chen). We thank Jou-Hui Yu for technical assistance and Edanz Group (www.edanzediting.com/ac) for editing this manuscript.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

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Supplementary data