CD151 Expression Is Associated with a Hyperproliferative T Cell Phenotype Lillian Seu, Christopher Tidwell, Laura Timares, Alexandra Duverger, Frederic H. Wagner, Paul A. Goepfert, Andrew O. This information is current as Westfall, Steffanie Sabbaj and Olaf Kutsch of September 26, 2021. J Immunol published online 27 September 2017 http://www.jimmunol.org/content/early/2017/09/27/jimmun ol.1700648 Downloaded from

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The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2017 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published September 27, 2017, doi:10.4049/jimmunol.1700648 The Journal of Immunology

CD151 Expression Is Associated with a Hyperproliferative T Cell Phenotype

Lillian Seu, Christopher Tidwell, Laura Timares, Alexandra Duverger, Frederic H. Wagner, Paul A. Goepfert, Andrew O. Westfall, Steffanie Sabbaj, and Olaf Kutsch

The tetraspanin CD151 is a marker of aggressive cell proliferation and invasiveness for a variety of cancer types. Given reports of CD151 expression on T cells, we explored whether CD151 would mark T cells in a hyperactivated state. Consistent with the idea that CD151 could mark a phenotypically distinct T cell subset, it was not uniformly expressed on T cells. CD151 expression frequency was a function of the T cell lineage (CD8 > CD4) and a function of the memory differentiation state (naive T cells < central memory T cells < effector memory T cells < T effector memory RA1 cells). CD151 and CD57, a senescence marker, defined the same CD282 T cell populations. However, CD151 also marked a substantial CD28+ T cell population that was not marked by CD57.

Kinome array analysis demonstrated that CD28+CD151+ T cells form a subpopulation with a distinct molecular baseline and Downloaded from activation phenotype. Network analysis of these data revealed that cell cycle control and cell death were the most altered process motifs in CD28+CD151+ T cells. We demonstrate that CD151 in T cells is not a passive marker, but actively changed the cell cycle control and cell death process motifs of T cells. Consistent with these data, long-term T cell culture experiments in the presence of only IL-2 demonstrated that independent of their CD28 expression status, CD151+ T cells, but not CD1512 T cells, would exhibit an Ag-independent, hyperresponsive proliferation phenotype. Not unlike its reported function as a tumor aggressiveness marker,

CD151 in humans thus marks and enables hyperproliferative T cells. The Journal of Immunology, 2017, 199: 000–000. http://www.jimmunol.org/

cell homeostasis is essential to maintain the naive T cell proteins, including kinases (10–15) and phosphatases (16–20). (TN) population, as well as the T cell populations that Misalignment of any of the components that form this highly T constitute our immunological memory (1–4). In healthy complex network can result in increased T cell proliferation, a individuals, T cell homeostasis is tightly controlled through the lowered threshold for Ag activation, or a loss of immune tolerance integration of a wide variety of mechanisms. Homeostatic T cell and the development of autoimmune phenotypes (8, 21, 22). A proliferation is driven by various combinations of cytokines and protein family that has a functional profile compatible with low-affinity interactions with self-antigen (5–8). Accordingly, influencing the T cell activation state via their ability to mobilize by guest on September 26, 2021 known receptors involved in T cell homeostasis include, but are intracellular T cell signaling molecules would be tetraspanins, but certainly not limited to, cytokine receptors such as IL-7R or IL- a potential role of tetraspanins in T cell homeostasis or mis- 15R (9), the TCR, as well as costimulatory molecules such as alignment thereof has not been explored. CD28. At the cellular level, the involved signaling pathways that In mammalians, tetraspanins are a family of 33 different small transduce these signals into the cells involve a plethora of different proteins with 4 transmembrane-spanning domains that are known to regulate cell morphology, motility, invasion, and fusion, and that Department of Medicine, University of Alabama at Birmingham, Birmingham, AL are involved in cell proliferation and apoptosis in a variety of 35294 different cell types (for reviews, see Refs. 23–28). Tetraspanins ORCIDs: 0000-0002-8456-019X (L.S.); 0000-0002-9739-2244 (C.T.); 0000-0001- have an exceptional ability to coordinate cell surface molecules 8886-8354 (L.T.); 0000-0001-8441-5737 (P.A.G.); 0000-0002-0468-4695 (A.O.W.); 0000-0003-4052-6819 (S.S.); 0000-0002-1853-8023 (O.K.). laterally binding to other tetraspanins or to other membrane pro- Received for publication May 4, 2017. Accepted for publication August 28, 2017. teins (integrins, CD2, CD4, CD8, CD5, CD19, CD21, Fc recep- This work was supported by National Institutes of Health (NIH) Grants F32 tors, MHC class I, and MHC class II) (reviewed in Ref. 26) to HL121924 (to L.S.) and R01-AI104499, R56-AI122842, and R21-AI116188 (to form the highly specialized structure known as tetraspanin-enriched O.K.). Parts of this work were performed in the University of Alabama (UAB) Center microdomains (29, 30) or tetraspanin webs (31). Tetraspanins, likely for AIDS Research BSL-3 facilities and by the UAB Center for AIDS Research Flow Cytometry Core/Joint UAB Flow Cytometry Core, which are funded by NIH/ as a function of the cell type, have been described to influence Rac, National Institute of Allergy and Infectious Diseases Grant P30 AI027767 and by PKC, and CDC42 activity (32, 33) or Ras, ERK/MAPK1/2, and NIH Grant 5P30 AR048311. protein kinase B/Akt signaling (34, 35). Also, PKCa or PI4K has The microarray data presented in this article have been submitted to the ArrayEx- press database (https://www.ebi.ac.uk/arrayexpress/) under accession numbers E- been reported to associate closely with certain tetraspanins, includ- MTAB-5978 and E-MTAB-5977. ing CD9 and CD81 (23, 36, 37). Address correspondence and reprint requests to Dr. Lillian Seu and Dr. Olaf Kutsch, Some tetraspanins (CD9, CD37, CD81, CD151) have been Department of Medicine, University of Alabama at Birmingham, BBRB 510, 845 reported to be expressed on T cells, where their function has 19th Street South, Birmingham, AL 35294. E-mail addresses: [email protected] (L.S.) and [email protected] (O.K.) mostly been described using knockout mouse models. With only The online version of this article contains supplemental material. little experimental evidence having been accumulated using human T cells, it nevertheless seems clear that tetraspanins affect T cell Abbreviations used in this article: GO, Gene Ontology; IS, immunologic synapse; NIH, National Institutes of Health; PIN, protein–protein interaction network; TCM, activation in ways similar to costimulation (25, 38–42). We central memory T cell; TEM, effector memory T cell; TEMRA, T effector memory were particularly interested to detail the role of CD151 in T cell RA1 cell; T , naive T cell. N biology, because increased CD151 expression has been associated Copyright Ó 2017 by The American Association of Immunologists, Inc. 0022-1767/17/$35.00 with aggressive cell proliferation and invasiveness for a variety of

www.jimmunol.org/cgi/doi/10.4049/jimmunol.1700648 2 CD151 MARKS HYPERRESPONSIVE T CELLS different tumor types, suggesting that its altered expression may an intracellular protein that is exclusively expressed in cycling cells in the be linked to a hyperactivated T cell state. For example, increased late G1,G2, S, and M phases, and accordingly, it is absent in resting cells CD151 expression has been associated with tumor aggressiveness (G0) (57) and is therefore frequently used to detect actively cycling cells. Flow cytometric analysis and cell sorting experiments were performed in breast cancer, endometrial cancer, esophageal squamous cell using an LSR II flow cytometer and FACSAria II instrument, respectively carcinoma, epithelial malignancies, non–small cell lung cancer, (Becton Dickinson). Gates for flow cytometric acquisition and analyses pancreatic ductal adenocarcinoma, colon cancer, or prostate can- were based on “fluorescence-minus-one” controls and single-stain com- cer (43–51). Genetic ablation of CD151 expression has been pensation controls. Data were analyzed using FlowJo software (Tree Star, Ashland, OR). reported to reduce metastatic spread of cancer, providing func- tional evidence that increased CD151 expression may actively T cell proliferation assays contribute to this aggressive phenotype (52). In immunology, For proliferation assays, the T cells were labeled with 1 mM CFSE CD151 has been reported as a negative regulator of FcεRI-mediated (Invitrogen). Cells were plated at 5 3 105 cells per well in 96-well flat- mast cell activation (53). On T cells, CD151 has been shown to bottom plates and incubated for 5 d after addition of IL-2. The extent of stabilize the immunological synapse after T cell activation, and T cell proliferation is proportional to the decrease in CFSE fluorescence, silencing of CD151 blunts IL-2 secretion and expression of the with every cell division decreasing the CFSE fluorescence intensity of the daughter cells by 50%. The frequency of CFSElow T cells was used as a activation marker CD69 (54–56). Consistent with previous reports measurement of total T cell proliferation, and flow cytometry gates were that CD151 interacts and signals in combination with integrins, set using untreated control conditions as the baseline. For long-term IL-2 silencing of CD151 expression also diminished the relocalization culture experiments, IL-2 (30 U/ml) was added every 2–3 d, and samples of a4b1 integrin to the immunologic synapse (IS), which resulted were harvested at the indicated time points of the 31-d experimental pe- in reduced phosphorylation of the integrin targets FAK and riod. Upon harvesting, cells were washed, labeled with specific mAbs Downloaded from (CD3, CD4, CD8, CD28, and CD151), and subjected to flow cytometric ERK1/2 (54). analysis. In this article, we demonstrate that CD151 is expressed on a subset of T cells and once expressed, actively alters the molecular Generation of CD151-overexpressing T cells signaling phenotype of these cells. Different from other tetraspa- The expression plasmid pMSCV-CD151 was constructed by cloning the nins, such as CD37 or CD81 that are ubiquitously expressed on all cDNA sequence coding for human CD151 into a murine stem cell virus- derived retroviral vector (pMSCVpuro; Clontech) using standard PCR T cells, we demonstrate that CD151 on T cells differentially marks http://www.jimmunol.org/ 9 9 specific subpopulations within both CD4 and CD8 lineages and techniques (5 Xho1-GAAACTCGAGatgggtgagttcaacgagaagaag; 3 EcoR1-ATTCGAATTCtcagtag-tgctccagcttgagac). pMSCV-CD151 was throughout all differentiation states. In line with the role of CD151 cotransfected with pHIT60 (gag/pol) and pVSV-G into HEK-293T cells as a marker of tumor aggressiveness, we demonstrate that CD151 is using FuGENE 6 Transfection Reagent (Promega) to produce retroviral involved in active outside-in signaling and that CD151+ T cells vector particles. Culture supernatants containing retroviral CD151-vector particles were harvested 2–4 d posttransfection and used to transduce exhibit increased proliferative propensity in the absence of Ag- + high specific TCR activation even in CD282 cells, which are believed Jurkat CD4 T cells. Sorted CD151 Jurkat cells and mock-transduced Jurkat cells were used for subsequent kinome analysis. to be senescent. Consistent with its role in cancer, CD151 in hu- mans thus marks and enables hyperresponsive T cells. Our data Kinex Ab microarray analysis by guest on September 26, 2021 further suggest that in humans, expression of CD151 on selective To perform kinome analysis using Kinex microarrays, we labeled 50 mg T cell subsets provides a so far unrecognized component of the of lysate protein from each sample with a proprietary fluorescent dye signaling network that influences T cell homeostasis. according to the manufacturer’s instructions (Kinexus, BC, Canada). The used KAM-850 chips were spotted in duplicates with .850 Abs: 510 pan- specific Abs used in the chip allow for the detection of 189 protein kinases, Materials and Methods 31 protein phosphatases, and 142 regulatory subunits of these enzymes and Cell culture and isolation of primary peripheral bloods cells other cell signaling proteins. A total of 340 phospho-specific Abs tracked the unique phosphorylation of 128 sites in protein kinases, 4 sites in protein All cells were maintained in RPMI 1640 supplemented with 2 mM phosphatases, and 155 sites in other cell signaling proteins. The background- L-glutamine, 100 U/ml penicillin, 100 mg/ml streptomycin, and 10% heat- corrected raw intensity data were logarithmically transformed with base 2. Z inactivated FBS. Cryopreserved PBMCs from healthy adults were obtained scores were calculated by subtracting the overall average intensity of all through the University of Alabama Clinical Sample Repository, after local spots within a sample from the raw intensity for each spot, and Z score ratios institutional review board approval was obtained and all donors had con- were calculated by dividing Z scores by the SDs of all of the measured sented to this study. For some of the studies, PBMCs derived from buffy intensities within each sample. To minimize unspecific background signals, coats were used (Research Blood Components, Brighton, MA). PBMCs we harvested three lysates from Jurkat and three lysates from J-CD151 cells were isolated from peripheral blood using Ficoll-Paque Plus density gra- at different growth stages and pooled them to provide one sample for Jurkat dient centrifugation (GE Healthcare Life Sciences, Uppsala, Sweden) and and one sample for J-CD151 cells before loading on the Kinexus Ab were cryopreserved. For the experiments, cryopreserved PBMCs were microarray. The ArrayExpress accession number for the dataset is E-MTAB- thawed, counted, and assessed for viability with a Guava EasyCyte flow 5978 (https://www.ebi.ac.uk/arrayexpress/). To minimize unspecific back- cytometer (EMD Millipore, Billerica, MA). Lymphocyte viability ranged ground signals in the kinome analysis of primary T cells, CD4+CD1512 and from 85 to 95%. CD4+CD151+ T cells from five different healthy donors were each sorted + 2 + + Flow cytometric analysis and reagents and the lysates from all CD4 CD151 T cells and from all CD4 CD151 T cells were pooled before loading on the Kinexus Ab microarray. The LIVE/DEAD Fixable Aqua Stain (Invitrogen, Carlsbad, CA), excited by ArrayExpress accession number for the dataset is E-MTAB-5977 (https:// violet 405 nm laser and detected by 512 nm emission channel, was used to www.ebi.ac.uk/arrayexpress/). exclude dead cells from analysis. The T cell phenotype was determined by All kinome data that were used for Gene Ontology (GO)-motif analysis staining with mAbs: CD3-allophycocyanin efluor780 (UCHT1; eBio- or to generate protein–protein interaction networks (PINs) are available in science, San Diego, CA), CD4-V500 (RPA-T4 or SK3; BD Biosciences, Supplemental Tables I–VII. GO-motif analysis and PINs were generated Franklin Lakes, NJ), CD151-PE (14A2.H1; BD Biosciences), and CD25- using MetaCore software (Thomson Reuters). In the presented studies, we FITC or -allophycocyanin (M-A251; BD Biosciences). Abs recognizing exclusively used the MetaCore direct interaction algorithm to link the CD45RA-allophycocyanin (HI100; BD Biosciences) and CCR7-PerCp- proteins that were found altered in our kinome array analysis experiments + Cy5.5 (150503; BD Biosciences) were used to define TN (CD45RA into a network. This algorithm uses only proteins that are uploaded to + 2 + CCR7 ), central memory T cells (TCM; CD45RA CCR7 ), effector generate a PIN and does not allow for the computational inclusion of 2 2 1 memory T cells (TEM; CD45RA CCR7 ), and T effector memory RA additional proteins during the network generation process. Detailed pro- + 2 cells (TEMRA; CD45RA CCR7 ). Intracellular staining of the prolifera- cedures have been previously described by our group (58). tion Ag Ki-67-FITC (B56; BD Biosciences) was performed using the BD Notably, to demonstrate that the MetaCore direct interaction algorithm Cytofix/Cytoperm kit according to the manufacturer’s protocols. Ki-67 is that was used for the analysis of our kinome data cannot produce a network The Journal of Immunology 3 from a list of random genes, we attempted to build a network from a list of erally found to be CD151+. However, other than CD57, which was genes that served as HIV-1 integration sites in patients (59). HIV-1 is known mostly expressed on CD282 T cells, CD151 also marked a CD28+ to integrate into actively expressed genes; however, no strong integration T cell subpopulation, suggesting that CD151 has a unique ability site bias has been reported, and as such this gene list can be considered 2 + random. As shown in Fig. 3A, the direct interaction algorithm (or for that to mark not only “senescent” CD28 CD57 T cells, but also to matter more complex one-step or two-step algorithms) was not able to link resolve the CD28+ T cell population into two previously unrec- this random list of genes into a network. ognized subpopulations. Statistical analysis The association of CD151 expression with CD28 expression status and CD57 expression with CD28 expression status for a total Statistical analyses to determine all differences (e.g., CD151 or Ki-67 of 20 donors for CD4+ T cells and CD8+ T cells is shown in expression frequency) were performed using a Student t test. Enrichment of CD151 cell surface expression across memory subsets was assessed by Fig. 2B and 2C, respectively. The data clearly demonstrate that repeated measures ANOVAwith Bonferroni multiple comparisons posttest CD151 also marks a phenotypically nonsenescent subpopulation 2 correction. Correlation analyses for normally distributed CD151 induction of CD28+CD57 T cells. The size of the CD4+CD28+CD151+ data were performed using Pearson correlation coefficient. The statistical T cell population was on average 23.3% (range: 8–48%), whereas software used was GraphPad Prism v5.0d (GraphPad Software, La Jolla, + + + , the size of the CD8 CD28 CD151 T cell population was on CA). The p values for all statistical analyses are depicted as follows: *p + + 0.05, **p , 0.01, ***p , 0.001. average 33.8% (range: 12–67%). The corresponding CD4 CD28 CD57+ and CD8+CD28+CD57+ T cell populations were 2.7 and 4.9% in size, respectively (p , 0.0001). These findings imply that, Results although CD151 expression can also be expressed on senescent 2 CD151 expression patterns as a function of T cell lineage and CD28 CD57+ T cells, rather than being a senescence or ex- Downloaded from differentiation state haustion marker, CD151 seems to provide a unique phenotype or CD151 has been reported to be uniformly expressed on a variety of functionality that is shared between senescent and nonsenescent cell types. Increased expression levels of CD151 have been as- T cells. sociated with a series of cancers, and higher CD151 expression Kinome array analysis reveals massive differences in the levels have been associated with tumor aggressiveness (43–51). As 2 molecular networks controlling CD151+ and CD151 T cells a marker for functionally distinct T cell populations, CD151 http://www.jimmunol.org/ would have to be either expressed at different expression levels on The T cell population that is resolved only by CD151 and not by the + distinct populations (high/low) or CD151 would have to be present previously described senescence marker CD57 is the CD28 + on distinct T cell subpopulations, independent of the expression CD151 population. Therefore, to develop an initial understanding + + level. Given reports that CD151 expression contributes to the of the molecular biology of T cells that exhibit a CD28 CD151 stability of the IS (54, 55), we had expected CD151 to be phenotype, we used kinome array analysis to describe the system- 2 expressed on all T cells, but surprisingly, CD151 marked distinct wide differences in the molecular signaling networks of CD151 + subpopulations. CD151 was expressed in a lineage-dependent and CD151 T cells. Because kinome array analysis requires a manner, with a higher percentage of CD8+ T cells being high amount of cell material and our data suggested a similar role

+ + + by guest on September 26, 2021 CD151+ at baseline (∼60%; range: 26–82%) than CD4+ T cells of CD151 for CD4 and CD8 T cells, we opted to sort for CD4 + + 2 (∼25%; range: 6–43%) (Fig. 1A). To assess CD151 expression CD151 and CD4 CD151 T cell populations, which are more + frequency as a function of the T cell differentiation state, we used abundant than the equivalent CD8 T cell populations. Cells from Abs recognizing CD45RA and CCR7 to define TN,TCM,TEM, and five healthy donors were obtained, sorted, and subjected to kinome TEMRA. As shown in Fig. 1B, within each of the two T cell array analysis. lineages, the CD151 expression frequency increased with the To understand baseline differences in the protein networks, we + 2 + + T cell differentiation state. TN populations held the lowest number compared the kinomes of CD4 CD151 and CD4 CD151 T cells + + of CD151 T cells, and TEMRA populations were highly CD151 . (Supplemental Table I). A total of 104 signals were found altered + 2 + + Given the contribution of the various memory T cell populations between CD4 CD151 and CD4 CD151 T cells either at the to the total CD4+ or CD8+ T cell populations (data not shown), level of protein expression or phosphorylation. Note that some this means that the majority of CD4+CD151+ T cells are either signals pertain to the same protein, as for some proteins several + + TCM or TEM, whereas the majority of CD8 CD151 T cells are Ab spots are found on the chip. Network analysis using the found in the TEM and TEMRA populations (Fig. 1C). This differ- MetaCore direct interaction algorithm that creates a network using ential expression of CD151 would allow for the possibility that only the objects in the list of altered proteins confirmed the quality CD151 marks a particular T cell phenotype that would emerge in of the kinome data. A random list of proteins would not connect or the CD4+ and CD8+ T cell lineages and in all memory differen- may connect in small groups, but not a network (Fig. 3A). In the tiation states. PIN using the direct interaction algorithm that describes the dif- ference between CD1512 and CD151+ T cells, all but 4 of 104 CD151 expression as a function of CD28 or CD57 expression different seed nodes linked up into a single network (Fig. 3B). To further our contextual understanding of CD151 expression, we Overall, in CD151+ T cells, more kinases, transcription factors, or next determined CD151 expression on T cells in relation to other phosphatases were found expressed at a lower level or less key T cell markers that have been associated with defined func- phosphorylated (61) rather than increased (42) in the absence of tional states. Given the increased frequency of CD151 in more any stimulus, possibly indicative of a resting phenotype (Fig. 4A). differentiated T cell populations, we were particularly interested in This would be consistent with the findings that CD151 is more the relationship of CD151 with senescence markers. Loss of CD28 likely expressed on differentiated memory T cells or is somewhat expression is considered a hallmark of T cell senescence. We found associated with a senescent phenotype. Network analysis identi- that CD4+CD282 T cells and CD8+CD282 T cells were mostly fied the Btk/b-catenin/PKC/FAK2 pathway (associated with pos- CD151+ (Fig. 2A) with some variations among donors (Fig. 2B). itive regulation of response to stimulus [p = 1.378 3 10232]) and CD151 expression in both CD4+ and CD8+ T cells was also linked the ATF-2/QIK/CaMKII/b-catenin/ATF-2/c-Jun pathway (associ- to CD57 expression, a positive marker of senescent T cells (60), ated with positive regulation of cellular metabolic process [p =1. and CD4+CD57+ and CD8+CD57+ T cell populations were gen- 380 3 10227]) as the highest ranked curated pathways associated 4 CD151 MARKS HYPERRESPONSIVE T CELLS

FIGURE 1. CD151 marks T cell pop- ulations independent of lineage commit- ment and memory differentiation state. (A) Lineage-dependent expression of CD151 was determined by quantifying the per- centage of CD4+CD151+ and CD8+CD151+ T cells for a total of 28 healthy human donors. (B) The frequency of CD151+ T cells as a function of the memory differentiation state was determined for a total of 16 healthy donors. T cell subsets are defined by patterns of CD45RA and + + CCR7 expression: TN (CD45RA CCR7 ), 2 + 2 TCM (CD45RA CCR7 ), TEM (CD45RA

2 + – Downloaded from CCR7 ), and TEMRA (CD45RA CCR7 ). A possible association of the percentage of CD151+ T cells with the different memory T cell populations was analyzed using repeated measures ANOVA statistical analysis with a Bonferroni multiple comparisons posttest correction. (C) Pie charts showing the abso- lute contributions of the T cell memory http://www.jimmunol.org/ subsets to the total CD151+ T cell pop- ulation. *p , 0.05, **p , 0.01, ***p , 0.001. by guest on September 26, 2021 with the list of identified altered proteins. Consistent with these The analysis was done using the same sorted donor T cell material pathway motifs, the highest ranked network hubs were p53, c-Jun, (five donors) that was used for the analysis of phenotypic molecular STAT3, and b-catenin (Fig. 3C). GO enrichment analysis ranked differences between CD1512 and CD151+ Tcells.TheCD1512 or regulation of programmed cell death and regulation of cell cycle CD151+ T cells from each donor were exposed to IL-2 (30 U/ml) as the highest ranked specific motif changes, and positive regu- for 24 h, harvested, and subjected to kinome analysis. lation of MAPK cascade as the highest specific biological process Because IL-2 responsiveness in vivo is thought to depend on the that would be associated with the observed protein changes be- previous recognition of cognate Ag, IL-2 exposure by itself should tween CD1512 and CD151+ T cells. Sixty-four percent of the only cause a limited amount of changes in the signal transduction proteins found altered in their expression or phosphorylation state network. This was indeed the case for CD1512 T cells, where 63 were involved in programmed cell death (p = 5.660 3 10224), low-amplitude differences between untreated and IL-2–treated 46% of the altered proteins were associated with cell proliferation cells were recorded (Fig. 4B, upper graph, Supplemental Table II). (p = 19.630 3 10218), and 27% of the altered proteins were in- However, consistent with the baseline kinome motifs of CD151+ volved in the MAPK signaling (p = 1.115 3 10210). T cells (positive regulation of response to stimulus), addition of Because the network analysis of the kinome studies demon- IL-2 resulted in an exaggerated response (Fig. 4B). For CD151+ strated that CD151+ cells were associated with a positive regula- T cells, a total of 110 differential signals with a larger signal tion of response to stimulus, we next compared the response of amplitude range were recorded than observed for CD1512 T cells CD1512 T cells and CD151+ T cells to IL-2 stimulation. IL-2 is (104/110 linked; Supplemental Table III), suggesting that CD151+ considered signal 3 in the T cell activation process and is thought T cells are hyperresponsive to IL-2 without a requirement for to mostly sustain proliferation of T cells that have been activated cognate Ag recognition (Fig. 4B, lower panel). The top three GO by TCR recognition of their cognate Ag, followed by proper co- motifs that were associated with the IL-2–induced changes in stimulation through CD28 receptor engagement by CD80 or CD86 CD151+ T cells were regulation of cell death (p = 3.108 3 10222), on the APC. Resting T cells have no or only low levels of the high- MAPK cascade (p = 2.720 3 10222), and regulation of cell pro- affinity IL-2R CD25, but express the low-affinity IL-2R CD122. liferation (p = 3.660 3 10220). When we detailed the IL-2 re- IL-2 exposure was intended to investigate possible response dif- sponse (Fig. 4C), we found that CD1512 and CD151+ T cells ferences to immunologically relevant nonantigen stimuli that actually shared a total of 28 proteins that were dynamically al- would be expected to be present at elevated concentrations in tered by IL-2 (Supplemental Table IV). In addition, 29 regulated lymph nodes, but would be mostly absent in the peripheral blood proteins were unique to the CD1512 T cell response, but the and would not be considered a cytokine typically associated with changes were all in the low dynamic range (Supplemental Table V). homeostatic proliferation (61–63). In contrast, a total of 81 proteins were found uniquely altered in The Journal of Immunology 5

FIGURE 2. CD151 expression marks a unique CD28+ T cell population. With loss of CD28 and increase in CD57 expression being the classic markers of T cell senescence, we detailed the association of these markers with CD151 on CD4+ or CD8+ T cells. (A) Dot plot analysis shows the representative paired cell surface expres- sion patterns of CD28/CD151, CD28/CD57, andCD57/CD151onCD4+ and CD8+ T cells from a representative donor. (B)CD151and CD57 expression frequencies on T cells from

20 donors are compared as a function of CD28 Downloaded from expression demonstrating that CD151 marks a CD28+ T cell population that is not recognized by CD57. (C)Asimilaranalysisasin(B)was performed for CD8+ T cells. http://www.jimmunol.org/

CD151+ T cells in response to IL-2, and the observed changes of changes in the phosphorylation state of the altered proteins, rather by guest on September 26, 2021 were more dynamic than those observed in CD1512 T cells (Fig. than in the regulation of protein expression, when we compared 4C, lower panel, Supplemental Table VI). these data with previously published kinome analysis experiments To our knowledge, these system-wide data provided the first from our group or the other kinomic data presented in this study (58, evidence that CD151+ T cells, which are found throughout all 64, 65). Out of the 47 altered signals, 33 signals indicated differ- T cell differentiation states, are phenotypically different from ences in the phosphorylation state, all of which showed increased CD1512 T cells. At baseline, consistent with the higher frequency phosphorylation. Similarly, all of the 14 signals that indicated of CD151+ T cells in resting or senescent memory T cell pop- changes in protein expression were upregulated signals. In line with ulations, CD151+ T cells seemed to be less activated; however, in the idea that CD151 would provide an activating signal, CD151 the presence of IL-2, CD151+ T cells exhibited a hyperresponsive overexpression exclusively resulted in signal increases. molecular phenotype. Also in line with the data we obtained when we compared primary CD151+ and CD1512 T cells, analysis of the direct in- CD151 expression actively changes the host cell phenotype teraction network that was altered in J-CD151 when compared Even though the transcription factor signature that drives CD151 with the parental control cells (45/47 seed nodes connected), the expression could alter the baseline and response phenotype of highest ranked specific GO process motifs were regulation of CD151+ T cells, we wanted to investigate whether CD151 would programmed cell death (52.50% of altered proteins; p = 4.111 3 just be a passive marker or an actively signaling molecule on 10212) and regulation of cell proliferation (50% of altered pro- T cells. Reports describing CD151 interaction with PIK4 or PKC teins; p = 1.843 3 10210). The MAPK cascade GO motif phe- signaling make the latter idea a distinct possibility (23, 36, 37); notype observed in primary CD151+ T cells was also reproduced however, none of these findings came from experiments using (27.50% of altered proteins; p = 7.170 3 10210). As shown in T cells. To determine a possible impact of CD151 expression on the Fig. 5C and 5D, the phenotypic changes predicted by network signaling network of T cells, we generated CD151-overexpressing analysis based on the signal changes detected by kinome analysis Jurkat T cells (J-CD151; Fig. 5A). were indeed predictive of functional changes. Consistent with the Relative to the parental Jurkat T cells and a Jurkat T cell GO motif analysis, J-CD151 cells had: 1) a higher proliferative population that was transduced with an empty retroviral vector, capacity and 2) exhibited increased viability. When we compared forced expression of CD151 caused a total of 47 changes to the cell proliferation capacity, starting at low input cell numbers (1 3 signaling network of J-CD151 cells (Fig. 5B; only proteins that 103 cells/ml) that allowed the T cells to remain in the exponential remained unaltered in mock-transduced cells relative to Jurkat growth phase during the experimental period, J-CD151 T cells cells, but were altered in J-CD151 cells were considered; proliferated at a significantly higher rate (Fig. 5C). Also, when Supplemental Table VII). There were two striking observations. compared with the parental Jurkat T cells, J-CD151 cells exhibited CD151 overexpression resulted in an unprecedented relative level an overall increased viability (Fig. 5D). 6 CD151 MARKS HYPERRESPONSIVE T CELLS Downloaded from http://www.jimmunol.org/

FIGURE 3. PIN describing the altered baseline phenotype of CD151+ T cells. (A) Negative control reference data set for direct interaction algorithm- by guest on September 26, 2021 generated networks. HIV-1 is known to integrate into actively expressed genes; however, no strong integration site bias has been reported and as such this gene list can be considered random. The MetaCore direct interaction algorithm that was used for the analysis of our kinome data cannot produce a network from a list of genes that were described as HIV-1 integration sites by Han et al. (59). (B) CD4+ T cells from a total of five donors were sorted to obtain CD4+ CD1512 and CD4+CD151+ T cell populations. To reduce unspecific background signals, we pooled lysates from the CD1512 T cell populations or the CD151+ T cell populations, respectively, before loading the lysate mixes on Kinexus Ab arrays. The proteins that were found differentially expressed or phosphorylated in CD151+ T cells when compared with CD1512 T cells were then used as seed nodes to generate a PIN using a direct interaction algorithm in MetaCore. The seed nodes marked by a gray circle indicate altered protein signals associated with a GO enrichment cell proliferation motif. Red arrows indicate seed nodes associated with the MAPK cascade. (C) The table insert lists the key hubs of the network. Edges refer to the number of connections that an individual hub has in the network (green: numbers of outgoing [controlling] connections; red: numbers of incoming [controlled by] connections).

These data clearly demonstrate that CD151 is not only a passive proliferation, IL-2 would not stimulate growth of T cells that were marker, but that CD151 in this system actively signaled to alter not previously Ag experienced (or PHA-L/anti-CD3/CD28 mAb T cells in a manner similar to the differences observed between activated), but would continuously drive T cell cycling over primary CD1512 and CD151+ T cells, with phenotypic changes several months after the T cells were activated by cognate Ag mostly pertaining to a cell proliferation and a cell survival phe- (61–63). notype. The data also validated the predictive analytical capacity CFSE experiments over 5 d using T cells derived from four of kinome analysis–based pathway motif analysis. healthy donors did not show significant induction of CD151 expression by IL-2 alone, but consistent with the kinome data, CD151 marks hyperresponsive, unchecked T cells demonstrated that IL-2–induced T cells underwent at least one To challenge the kinome analysis–derived prediction that primary round of cell proliferation during this experimental period CD151+ T cells differ from CD1512 T cells either in their ability (Fig. 6A). As similar cultures were extended to day 31, we to proliferate or in their ability to survive, we initiated long-term followed the relative contribution of the CD151+ and the cultures using primary T cells from four donors. In these experi- CD1512 T cell subpopulations to the total T cell population. To ments, the T cells were not stimulated by polyclonal activators obtain information on the senescence status of the respective such as PHA-L or anti-CD3/CD28 mAb combinations, but cul- T cell populations, we further resolved the T cell populations for tured in the presence of only IL-2 (30 U/ml), which is a known their CD28 status (Fig. 6B, 6E), and to determine whether survival factor for T cells. IL-2 was the first reported mitogenic changes in the size of the four different CD28+/2CD151+/2 lymphokine known that was shown to stimulate T cells to undergo populations would be associated with proliferative capacity, we cell cycle progression. However, other than IL-7 or IL-15, which stained for the proliferation marker Ki-67 on day 14 of the ex- have been reported to drive Ag-independent homeostatic T cell periments (Fig. 6C, 6F). The Journal of Immunology 7 Downloaded from http://www.jimmunol.org/

FIGURE 4. CD151 expression–associated protein regulation profiles. Graphic depiction of the differential regulation of protein expression and protein phosphorylation states for the various experimental conditions describing differences in the absence or presence of IL-2 stimulation for CD1512 and CD151+ by guest on September 26, 2021 T cells. Lowered Z ratios (24.0 to 21.0) derived from the respective kinome array analysis experiment, which represent protein states that are downregulated in CD151+ T cells relative to CD1512 T cells, are assigned a blue color, with the lowest Z ratio = 24.0 being represented by the dark blue bar under the map. Similarly, protein states with an increased Z ratio (1.0–4.0) (42 proteins) are assigned a red color with the highest Z ratio = 4.0 being represented by the dark orange bar under the map. Barcode representations indicate phosphorylation signals in orange and assign each altered protein signal to the MAPK pathway (crimson), cell death/apoptosis (gray), or cell proliferation/cell cycle (blue). (A) At baseline, in the absence of stimulation, 104 proteins were found altered in primary CD151+ T cells when compared with CD1512 T cells (see Supplemental Table I), of which 42 proteins provided an increased and 62 proteins a decreased signal. (B) Sixty-three protein signals were found altered in primary CD1512 T cells after stimulation with IL-2, of which 33 proteins provided an increased and 30 proteins a decreased signal (see Supplemental Table II). (C) A total of 110 protein states were altered in CD151+ T cells in response to IL-2 treatment, of which 60 proteins provided an increased and 50 proteins a decreased signal (see Supplemental Table III). (D) Detailed graphic depiction of the parts of the IL-2 response of primary T cells that were shared between CD1512 and CD151+ T cells (see Supplemental Table IV), which were unique to CD1512 T cells (see Supplemental Table V) and were unique to CD151+ T cells (see Supplemental Table VI).

For the first 5 d of this experiment, within the CD4+ T cell from CD4+ T cells, as the CD282 T cell populations significantly population, CD4+CD28+CD1512 T cells constituted the domi- contributed to the overall population (CD8+CD282CD1512: 16%, nant T cell population (∼80%; range: 26–82%); then their fre- range: 9–20%; CD8+CD282CD151+: 16%, range: 8–37%). quency dropped to contribute ,17% (range 3–24%) by day 14. Independent of these baseline differences, as in CD4+ T cells, Conversely, CD4+CD28+CD151+ T cells, which initially consti- both CD8+CD151+ T cell populations (CD28+/2CD151+) ex- tuted ∼17% (range: 8–23%) of the total CD4+ T cell population, panded, whereas both CD8+CD1512 T cell populations (CD28+/2 had increased to ∼80% (range: 74–95%) by day 14 and remained CD1512) contracted (Fig. 6E) over time in the presence of IL-2, at this level until day 31 of the experiment. Somewhat surpris- similar to the population dynamics observed in CD4+ T cells. ingly, the size of the CD4+CD282CD151+ T cell population, Thus, surprisingly, the ability to proliferate in response to IL-2, which constituted 0.1–2.4% of the initial T cell population, in- in the CD4+ or in the CD8+ T cell population, was not associated creased to contribute ∼13% of the total CD4+ T cell population on with the CD28 expression status (CD28+/2), but was rather was day 31 (range: 12–15%). The small CD4+CD282CD1512 T cell associated with the CD151 expression status. In either T cell population (1.3–3.7%) further decreased in size (Fig. 6B). These lineage, even CD282 T cells, which are considered to be in a data would suggest that CD4+ T cells in this experiment would state of replicative senescence by some, had proliferative capacity proliferate upon IL-2 exposure as a function of their positive in the presence of IL-2, if they expressed CD151. CD28+CD1512 CD151 status and not as a function of their CD28 status. T cells for neither T cell lineage exhibited a relevant propensity to These observations were confirmed in the CD8+ T cell pop- proliferate. CD282CD1512 T cell populations, although being ulation. Here the CD28/CD151 baseline composition differed measurable at the beginning of the experiment, in particular in the 8 CD151 MARKS HYPERRESPONSIVE T CELLS Downloaded from

FIGURE 5. PIN describing the effect of CD151 on the phenotype of T cells. (A) Jurkat T cells were retrovirally transduced to overexpress CD151. (B) Graphic depiction of the differential regulation of protein expression and protein phosphorylation states for the 61 proteins that were found altered by the expression of CD151. Lowered Z ratios (24.0 to 21.0) derived from the respective kinome array analysis experiment, which represents protein states that are downregulated in J-CD151 T cells relative to Jurkat T cells, are assigned a blue color, with the lowest Z ratio = 24.0 being represented by dark blue. http://www.jimmunol.org/ Protein states with an increased Z ratio (1.0–4.0) are assigned a red color. Barcode representations indicate phosphorylation signals in orange and assign each altered protein signal to the MAPK pathway (crimson), cell death/apoptosis (gray), or cell proliferation/cell cycle (blue). (C) Jurkat and J-CD151 cells were seeded at 1 3 103 cells/ml, and cell numbers after 6 d of culture were determined using a GUAVA EasyCyte flow cytometer. The results represent the mean 6 SD of four independent experiments. (D) Jurkat and J-CD151 cells were seeded at 1 3 103 cells/ml, and cell viability was determined after 6 d of culture using a GUAVA EasyCyte flow cytometer. The results represent the mean 6 SD of four independent experiments.

CD8+ T cell population, were eliminated from these cultures, CD28+CD1512 T cells undergo normal controlled responses to suggesting that CD151 may even provide a survival signal for TCR-independent stimuli, whereas CD151+ T cells, independent CD282 T cells, which would be consistent with the kinome data of their CD28 status, are hyperresponsive to at least IL-2 and by guest on September 26, 2021 that network changes observed in CD151+ T cells were associated exhibit a somewhat unchecked proliferation phenotype in the with cell survival or proliferative capacity. absence of TCR/CD3 stimulation. Although selective cell death in some of the populations cannot CD151 expression on actively cycling T cells be excluded as a factor contributing to the shifts in population size, Fig. 6C and 6D for CD4+ T cells and Fig. 6F and 6G for CD8+ If CD151, as indicated by our experiments, is a marker that predicts the propensity of T cells to proliferate in the absence of Ag, we T cells demonstrate that the changes in the T cell composition + were associated with a superior capacity of CD151+ T cells to would expect to see that ex vivo CD151 T cell populations are more likely to harbor cycling Ki-67+ T cells than CD1512 T cells. respond to IL-2 with entry into active cell cycle. At baseline (ex Although we would postulate that CD151+ T cells are more likely vivo), donors on average have ,2% of CD4+Ki-67+ or CD8+Ki- to cycle in a cytokine-rich environment such as a lymph node, we 67+ T cells (Fig. 7). In contrast, 14 d into the IL-2 long-term would still expect to see a certain level of Ki-67 enrichment in culture, 40% (range: 32–48%) of the CD4+CD28+CD151+ + + + peripheral blood. To test this idea, we obtained PBMCs from 15 T cells and 38% (range: 25–56%) of the CD8 CD28 CD151 + + + donors and compared the number of Ki-67 T cells in the CD151 T cells were Ki-67 and therefore actively cycling. Only 3% of + + + 2 + T cell populations with the number of Ki-67 T cells in the CD4 CD28 CD151 T cells (range: 1–6%) and 6% of CD8 2 + + 2 CD151 T cell population (Fig. 7). Notably, CD4 T cells from CD28 CD151 T cells (range: 1–16%) expressed Ki-67. A sta- healthy donors are largely CD28+, which precluded us from + 2 tistically meaningful analysis of the CD4 CD28 population on detailing a possible additional effect of the CD28 status on Ki-67 day 14 was not possible, because we could not acquire a sufficient expression. In this analysis, we found 0.8% of the CD4+CD1512 number of events. Nevertheless, these data clearly suggest that T cell population to be Ki-67+ (range: 0.1–1.7%), whereas 3.7% of + 2 CD151 T cells in comparison with CD151 T cells have increased the CD4+CD151+ population was Ki-67+ (range: 2.2–7.3%). A cycling capacity in the absence of TCR engagement. Notably, al- similar comparison was performed for the CD8+ T cell population. though knockdown of CD151 has been reported to decrease the In this study, we found 0.9% of the CD8+CD1512 T cell pop- ability of T cells to produce IL-2, the differences in proliferative ulation to be Ki-67+ (range: 0.3–2.3%), whereas 1.9% of the CD8+ 2 capacity between CD151+ and CD151 T cells in our experimental CD151+ population was also Ki-67+ (range: 0.8–2.8%). Overall, system would not be based on increased production of IL-2 by these data suggest that even in the peripheral blood CD151+ CD151+ T cells after external IL-2 stimulation, because extrinsic T cells have an increased propensity to proliferate. addition of IL-2 did not stimulate IL-2 production (data not shown). Given that T cells are not known to efficiently proliferate in the Discussion absence of cognate Ag, and that IL-2 is not a signal that has been Impaired T cell homeostasis can result in increased T cell pro- associated with homeostatic T cell proliferation, we conclude that liferation, a lowered threshold for Ag activation, or even in the loss The Journal of Immunology 9 Downloaded from http://www.jimmunol.org/ by guest on September 26, 2021

FIGURE 6. CD151 expression on T cells is associated with an increased proliferative capacity in the absence of TCR activation. (A) PBMCs from four donors were CFSE stained and then cultured for 5 d in the absence or presence of IL-2. Proliferation was then measured as a reduction of CFSE fluo- rescence intensity using flow cytometric analysis. The baseline gate was adjusted based on the majority population in untreated cell cultures, whereas the proliferation gates were adjusted using anti-CD3/CD28 mAb–stimulated PBMCs (data not shown). PBMCs from another four donors were cultured in the presence of IL-2 (30 U/ml), which was replenished every 2–3 d for a total of 31 d. At the indicated time points, the contribution of the four possible CD28+/2 CD151+/2 T cell populations to the total T cell population was assessed using flow cytometric analysis. (B) Kinetic changes in the CD28+/2 CD151+/2 Tcell composition of the CD4+ T cell populations are depicted as mean population percentage 6 SD and show an enrichment of the CD28+CD151+ T cell population over time. (C) On day 14, cells were stained for the expression of the proliferation marker Ki-67 as a function of CD151 expression to address whether the enrichment of the CD28+/2CD151+ T cell population was driven by proliferation effects. (D) The percentage of CD4+Ki-67–expressing cells for the four donors on day 14 expressed as a function of the CD28+ CD151+/2 expression status. (E) Kinetic changes in the CD28+/2 CD151+/2 TcellcompositionoftheCD8+ T cell populations are depicted as mean population percentage 6 SD and show an enrichment of the CD28+/2CD151+ T cell populations over time. (F) To address whether the observed enrichment of the CD28+/2CD151+ T cell populations was driven by proliferation effects, on day 14 cells were stained for the expression of the proliferation marker Ki-67 as a function of CD151 expression. (G) The percentage of CD8+Ki-67+–expressing cells for the four donors on day 14 expressed as a function of the CD28+/2CD151+/2 expression status. **p , 0.01. of immune tolerance and the development of autoimmune phe- lineages (Fig. 1). In either lineage CD151 was expressed on notypes (8, 21, 22). A marker that identifies T cells with an in- subpopulations of T cells representing all different differentiation creased capacity to spontaneously proliferate in the absence of Ag states (TN,TCM,TEM,TEMRA), albeit at significantly different stimulation would allow us to more specifically study these T cells frequencies (Fig. 1). The differentiation state– and lineage- and possibly devise strategies to correct this type of immune independent expression of CD151 suggests that the specific misalignment. In this article, we provide data that the tetraspanin transcriptional program that drives CD151 expression must be CD151 not only serves as a marker of hyperresponsive T cells independent of transcriptional programs that govern lineage dif- with an increased propensity to proliferate in the absence of Ag ferentiation, or transcription signatures that govern memory T cell recognition (Fig. 6), but also demonstrate that CD151 expression differentiation. This would be important criteria for a marker of actively contributes to this state (Fig. 5). hyperresponsive T cells, because T cell misalignment has been Consistent with the requirements of a marker, we found CD151 reported to occur at all T cells differentiation states, including TN to be expressed on subpopulations of the CD4 or CD8 T cell (3, 4, 66). 10 CD151 MARKS HYPERRESPONSIVE T CELLS

ences in their kinome signature when compared with control cells that were marked by a pronounced hyperphosphorylation phenotype (Fig. 5C). Consistent with the pathway motif results that suggested alterations in cell cycle control, J-CD151 cells indeed proliferated by 30% faster during exponential growth, which is rather surprising given that Jurkat cells are a highly aggressive tumor cell line with a doubling time of ,24 h. As such, the observed hyperproliferative, unchecked phenotype of primary CD151+ T cells observed in re- sponse to IL-2 treatment in long-term cultures and the differential kinome profile of CD151-expressing T cells may in part originate from an altered transcription factor signature (inside-out signaling), but certainly the active outside-in signal associated with CD151 expression should contribute to the increased proliferative baseline FIGURE 7. Association of Ki-67 and CD151 on peripheral T cells. capacity of CD151+ Tcells. Peripheral blood cells from 16 healthy donors was obtained; stained for An interesting question is how a molecule like CD151 that has expression of CD3, CD4, CD8, CD151, and Ki-67; and analyzed by flow not been described to have significant direct signaling capacity, but cytometry. (A) The percentage of CD4+Ki-67+ T cells as a function of their CD151 expression status for all donors. (B) The percentage of CD8+Ki-67+ has been reported to signal in complex with mostly integrin T cells as a function of their CD151 expression status for all donors. partners, could cause an altered baseline signal transduction net- work once expressed. CD151 function has been detailed in a series Downloaded from of publications that describe the interaction of the extracellular part We found CD151 to be expressed on parts of a T cell population of CD151 with the extracellular domain of integrins (67). These that has been described as senescent (CD282CD57+), but primarily CD151/integrin complexes have been found to be associated with we found CD151 to mark a significant part of the CD28+CD572 phosphoinositide 4-kinase (37) and with protein kinase C signal- T cell population that so far has been considered as uniform and ing (36, 68). Hemler and colleagues (36, 68, 69) have suggested + 2 fully functional. Analysis of CD151 and CD151 T cells at the that tetraspanin proteins such as CD151 have a transmembrane http://www.jimmunol.org/ signal transduction level using kinome analysis provided evidence linker function, where the extracellular portion of CD151 would that CD151-expressing T cells at baseline form a population with associate with the integrin, and the cytoplasmic tail determines the a distinct molecular phenotype (Fig. 4A) that exhibited an ex- specific consequences of integrin outside-in signaling. We would ceedingly strong molecular activation response after IL-2 expo- thus propose that the observed changes caused by the presence of sure (Fig. 4B). At baseline and after IL-2 stimulation, network CD151 on T cells are the result of lateral CD151/integrin interac- analysis suggested changes to the cell proliferation and survival tions that optimize the signaling capacity of the integrin network. capacity of CD151+ T cells. This molecular response phenotype In extension, our findings obviously imply that not only CD151, was functionally confirmed in IL-2–stimulated long-term T cell but likely also other tetraspanins, could have the ability to fine-tune cultures in which CD151+ T cells proliferated in the absence of T cell phenotypes. Notably, CD81 has already been shown to act as by guest on September 26, 2021 stimulation by cognate Ag (Fig. 6). Most importantly, under these a costimulatory molecule (70, 71). Similarly to CD151, the tet- culture conditions it was not the CD28 expression status, which raspanin CD81 is also recruited to the IS during TCR stimulation has been linked to T cell senescence or exhaustion, but the ca- (72), but there are no studies yet on how CD81 expression is pacity of T cells to proliferate in the absence of Ag that was as- regulated as a function of T cell lineage or memory differentiation sociated with the CD151 expression status. Both CD28+CD151+ state, such as the one we present in this article. The tetraspanin and CD282CD151+ T cells proliferated, a phenomenon that is CD9 is another possible modulator of T cell phenotype because more clearly visible in CD8+ T cells than in the CD4+ T cell CD9 in complex with integrins also has a role in IS formation population, which mostly lacks CD282 T cells. Conversely, nei- (54). Our findings suggest that beyond their reported role in IS ther in CD4+ nor in CD8+ T cell populations did we observe IL-2– formation, the tetraspanin/integrin composition on T cells likely induced proliferation of CD1512 T cells, independent of their plays a mostly unrecognized role in fine-tuning T cell respon- CD28 expression status. siveness and T cell homeostasis. The differential molecular baseline state and stimulation response behavior, based on CD151 expression, could have two explanations. Disclosures First, the transcriptional signature that drives CD151 expression The authors have no financial conflicts of interest. could alter the baseline phenotype and the response phenotype of CD151+ T cells. Although this is a distinct possibility, it is difficult to experimentally test. The challenge would be to distinguish be- References tween the phenotypic contributions of a multitude of other tran- 1. Cho, J. H., H. O. Kim, C. D. Surh, and J. Sprent. 2010. 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CD151 expression promotes a hyperproliferative T cell phenotype

Lillian Seu, Christopher Tidwell, Laura Timares, Alexandra Duverger, Frederic H. Wagner, Paul A. Goepfert,

Andrew Westfall, Steffanie Sabbaj, Olaf Kutsch

Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama

The following tables provide the kinome array data used for GO-motif analysis and the generation or the presented protein-protein interaction networks. Supplemental Table I: Baseline differences in the protein networks of CD151- and CD151+ T cells

Antibody Target Phospho Site Phospho- MAPK Cell Full Target Protein Name CD151- CD151+ Z-ratio Uniprot Link Cell death Codes Protein Name (Human) rylation cascade proliferation

1 PK154 IKKa T23 Inhibitor of NF-kappa-B protein-serine kinase alpha (CHUK) 3160 864 -3.86 O15111 2 PK050 MEK2 mouse T394 MAPK/ERK protein-serine kinase 2 (MKK2) (mouse) 12581 3635 -3.68 P36507 3 NN038-1 eIF2a Pan-specific Eukaryotic translation initiation factor 2 alpha 4224 1571 -2.92 P05198 4 PK097-3 PYK2 Y579 Protein-tyrosine kinase 2 1538 595 -2.81 Q14289 5 NK105-1 MEK6 Pan-specific MAPK/ERK protein-serine kinase 6 (MKK6) 1402 547 -2.79 P52564 6 NP001 CD45 Pan-specific Leukocyte common antigen CD45 receptor-tyrosine phosphatase (LCA, T200) 2529 984 -2.79 P08575 7 PN162 Catenin a S641 Catenin (cadherin-associated protein) alpha 1476 590 -2.71 P35221 8 PK072-1 Akt1 (PKBa) S473 RAC-alpha serine/threonine-protein kinase 5885 2356 -2.69 P31749 9 PK020-3 FAK S722 Focal adhesion protein-tyrosine kinase 2531 1043 -2.61 Q05397 10 PN114 4E-BP1 T45 Eukaryotic translation initiation factor 4E binding protein 1 (PHAS1) 1865 771 -2.61 Q13541 11 PK162 Chk1 S280 Checkpoint protein-serine kinase 1 3220 1340 -2.58 O14757 12 NN013 Caspase 3 Pan-specific Caspase 3 (apopain, cysteine protease CPP32) 1125 471 -2.58 P42574 13 PN188 HDAC5 S498 Histone deacetylase 5 1972 830 -2.55 Q9UQL6 14 PK049 MEK2 T394 MAPK/ERK protein-serine kinase 2 (MKK2) 2211 988 -2.37 P36507 15 NK079 Insulin ReceptorPan-specific b Insulin receptor beta chain 872 398 -2.32 P06213 16 NN108 STI1 Pan-specific Stress induced phosphoprotein 1 (Hsc70/Hsp90 organizing protein (Hop)) 1527 708 -2.26 P31948 17 NN006-1 BCL Pan-specific B-cell lymphoma protein 2 alpha 975 456 -2.24 P10415 18 PK049-2 MEK2 human T394 MAPK/ERK protein-serine kinase 2 (MKK2) 2502 1167 -2.24 P36507 19 NN023 Cdc34 Pan-specific Cell division cycle 34 (ubiquitin-conjugating ligase) 3224 1737 -1.79 P49427 20 NN098 SOD (Cu/Zn) Pan-specific Superoxide dismutase 1 1990 1089 -1.75 Q6ND84 21 NK140 PKCt Pan-specific Protein-serine kinase C theta 1704 938 -1.74 Q04759 22 NN021 Catenin b Pan-specific Catenin (cadherin-associated protein) beta 1 24504 13673 -1.67 P35222 23 NK102 MEK3b Pan-specific MAPK/ERK protein-serine kinase 3 beta isoform (MKK3 beta) 928 526 -1.65 P46734 24 PN159 p53 S37 Tumor suppressor protein p53 (antigenNY-CO-13) 5247 2980 -1.63 P04637 25 NK099-1 MEK1 Pan-specific MAPK/ERK protein-serine kinase 1 (MKK1) 1698 988 -1.57 Q02750 26 NN162 Jun Pan-specific Jun proto-oncogene-encoded AP1 transcription factor 1314 768 -1.56 P05412 27 NN102-NN124 STAT1 Pan-specific Signal transducer and activator of transcription 1 alpha 10892 6371 -1.53 P42224 28 NK025-2 CDK1 Pan-specific Cyclin-dependent protein-serine kinase 1 2666 1590 -1.49 P06493 29 NN110 TRADD Pan-specific Tumor necrosis factor receptor type 1 associated DEATH domain protein 1533 917 -1.49 Q15628 30 PN115 ATF2 S94/S112 Activating transcription factor 2 (CRE-BP1) 2146 1287 -1.47 P15336 31 PK165 CDK6 Y13 Cyclin-dependent protein-serine kinase 6 1145 689 -1.47 Q00534 32 PK093-1 PKCm (PKD) S916 Protein-serine kinase C mu (Protein kinase D) 9105 5520 -1.42 Q15139 33 PN171 c-Cbl Y700 Signal transduction protein CBL 1043 639 -1.41 P22681 34 PK072-3 Akt1 (PKBa) S473 RAC-alpha serine/threonine-protein kinase 1275 783 -1.40 P31749 35 NK141 PKCz Pan-specific Protein-serine kinase C zeta 8662 5320 -1.38 Q05513 36 NN083 p107 Pan-specific Retinoblastoma (Rb) protein-related p107 (PRB1) 3979 2495 -1.33 P28749 37 PK143 ASK1 S966 Apoptosis signal regulating protein-serine kinase 1 1131 722 -1.29 Q59GL6 38 PN057-2 p53 S392 Tumor suppressor protein p53 (antigenNY-CO-13) 2082 1328 -1.29 P04637 39 NP004 KAP Pan-specific Cyclin-dependent kinase associated phosphatase (CDK inhibitor 3, CIP2) 22327 14155 -1.28 Q16667 40 PN082-1 STAT3 Y704 Signal transducer and activator of transcription 3 7204 4587 -1.28 P40763 41 NN095 Smac/DIABLO Pan-specific Second mitochondria-derived activator of caspase 1049 675 -1.27 Q9NR28 42 PN143 PLCg2 Y753 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase gamma-2 1565 1014 -1.24 P16885 43 PN164 IkBa Y42 Inhibitor of NF-kappa-B alpha (MAD3) 493 324 -1.21 P25963 44 PK663 InsR Y1189 INSR insulin receptor 3910 2558 -1.20 P06213 45 NK101-3 MEK3 Pan-specific MAPK/ERK protein-serine kinase 3 beta isoform (MKK3 beta) 13267 8677 -1.19 P46734 46 NK249-2 SIK2 Pan-specific Serine/threonine-protein kinase SIK2 22760 14927 -1.17 Q9H0K1 47 NN104 STAT3 Pan-specific Signal transducer and activator of transcription 3 6358 4207 -1.16 P40763 48 PK089-1 PKCt S676 Protein-serine kinase C theta 1329 886 -1.16 Q04759 49 PN166 Catenin b S33 Catenin (cadherin-associated protein) beta 1 1484 990 -1.15 P35222 50 PK090-1 PKCt S695 Protein-serine kinase C theta 1272 850 -1.15 Q04759 51 PN079-PN136 STAT1 Y701 Signal transducer and activator of transcription 1 alpha 3512 2343 -1.14 P42224 52 PN101-2 Histone H3 T3 Histone H3.3 5549 3718 -1.12 P84243 53 NN121 Arrestin b Pan-specific Arrestin beta 1 1986 1350 -1.09 P49407 54 NP018 PP2Cd Pan-specific Protein-serine phosphatase 2C - catalytic subunit - delta isoform 1136 777 -1.08 O15297 55 PK055-1 Met Y1230/Y1234/Y1235Hepatocyte growth factor (HGF) receptor-tyrosine kinase 1384 948 -1.07 P08581 56 PN078-PN135 STAT1 S727 Signal transducer and activator of transcription 1 alpha 1752 1201 -1.07 P42224 57 PK072-5 Akt1 (PKBa) S473 RAC-alpha serine/threonine-protein kinase 10007 6836 -1.06 P31749 58 PK158 RSK1 T348 Ribosomal S6 protein-serine kinase 1 3002 2065 -1.05 Q15418 59 PN009 B23 (NPM) T234/237 B23 (nucleophosmin, numatrin, nucleolar protein NO38) 1682 1169 -1.03 P06748 60 NK027 CDK4 Pan-specific Cyclin-dependent protein-serine kinase 4 21337 14729 -1.02 P11802 61 PK152 IGF1R Y1280 Insulin-like growth factor 1 receptor protein-tyrosine kinase 4019 2799 -1.01 P08069 62 PK122-1 EGFR Y1068 Epidermal growth factor receptor-tyrosine kinase 2221 1553 -1.00 P00533 63 PK079-1 PKCd S645 Protein-serine kinase C delta 2709 3667 1.01 Q05655 64 NN153 KDEL Receptor (KR10)Pan-specific ER lumen protein retaining receptor 1 5389 7308 1.03 P24390 65 PK101-2 RSK1/2 S380/S386 Ribosomal S6 protein-serine kinase 1/2 1831 2549 1.09 Q15418 66 NN141-1 PDI Pan-specific Protein disulfide-isomerase 21029 29083 1.10 P07237 67 PN116 BRCA1 S1423 Breast cancer type 1 susceptibility protein 2969 4147 1.11 P38398 68 NN166 4E-BP1 Pan-specific Eukaryotic translation initiation factor 4E binding protein 1 (PHAS1) 770 1095 1.15 Q13541 69 NK156 B-Raf Pan-specific RafB proto-oncogene-encoded protein-serine kinase 7108 10093 1.17 P15056 70 NK099-8 MEK1 Pan-specific MAPK/ERK protein-serine kinase 1 (MKK1) 28486 40417 1.18 Q02750 71 PN022-2 Cortactin Y466 Cortactin (amplaxin) (mouse) 3301 4752 1.20 Q14247 72 PN041 Hsp27 S78 Heat shock 27 kDa protein beta 1 (HspB1) 13085 18808 1.21 P04792 73 PK587 CSF1R Y699 Macrophage colony-stimulating factor 1 receptor 1216 1772 1.23 P07333 74 NN028 Cyclin A Pan-specific Cyclin A1 25347 36646 1.24 P78396 75 PN051-1 MLC S19 Myosin regulatory light chain 2, smooth muscle isoform 6578 9620 1.26 P19105 76 PK549 BRSK1 T189 BR serine/threonine-protein kinase 1 3830 5676 1.29 Q8TDC3 77 PN036 Histone H2A.X S139 Histone H2A variant X 894 1351 1.34 P16104 78 PK732 Nek2 S171 NIMA (never-in-mitosis)-related protein-serine kinase 2 17408 26052 1.34 P51955 79 NN075 NT5E Pan-specific Ecto-5'-nucleotidase (CD73 antigen) 5838 8787 1.34 P21589 80 PK867 ERK1 S74 Extracellular regulated protein-serine kinase 1 (p44 MAP kinase) 5451 8341 1.39 P27361 81 NN136-2 Calnexin Pan-specific Calnexin 29173 44503 1.40 P27824 82 NN080 p27 Kip1 Pan-specific p27 cyclin-dependent kinase inhibitor 1B 5231 8101 1.43 P46527 83 NK227-2 LKB1 Pan-specific Serine/threonine-protein kinase 11 22829 35307 1.44 Q15831 84 NK137 PKCg Pan-specific Protein-serine kinase C gamma 9980 15512 1.45 P05129 85 NK181-4 TYK2 Pan-specific Protein-tyrosine kinase 2 (Jak-related) 27398 43928 1.55 P29597 86 PN028-1 eIF2a S52 Eukaryotic translation initiation factor 2 alpha 3192 5218 1.59 P05198 87 NN030-1 Cyclin D1 Pan-specific Cyclin D1 (PRAD1) 9954 16296 1.61 P24385 88 NN131 I2PP2A (PHAPII)Pan-specific Protein SET 17650 28878 1.61 Q01105 89 PN049-PN112-2 MAPKAPK2 T334 Mitogen-activated protein kinase-activated protein kinase 2 alpha 1402 2354 1.66 P49137 90 NN149-2 Crystallin aB Pan-specific Crystallin alpha B (heat-shock 20 kDa like-protein) 3925 6599 1.68 P02511 91 PN003-PN004 Adducin a/g S662 Adducin alpha (ADD1) 3710 6251 1.68 P35611 92 NK136-2 PKCe Pan-specific Protein-serine kinase C epsilon 4913 8314 1.70 Q02156 93 NK022 CaMKK Pan-specific Calcium/calmodulin-dependent protein-serine kinase kinase 4886 8350 1.73 Q8N5S9 94 PK102 RSK1/2/3 T573 Ribosomal S6 protein-serine kinase 1/2/3 315 560 1.82 Q15418 95 NK019-2 CAMK2d Pan-specific Calcium/calmodulin-dependent protein-serine kinase 2 delta 2324 4156 1.86 Q13557 96 NK014 Btk Pan-specific Bruton's agammaglobulinemia tyrosine kinase 10228 18418 1.90 Q06187 97 PK073 PKCa S657 Protein-serine kinase C alpha 3917 7650 2.13 P17252 98 NK135 PKCd Pan-specific Protein-serine kinase C delta 6982 13787 2.17 Q05655 99 PN155 Jun Y170 Jun proto-oncogene-encoded AP1 transcription factor 672 1458 2.43 P05412 100 NN155 MEF-2 Pan-specific Myelin expression factor 2 (MYEF2) 5073 11199 2.51 Q9P2K5 101 PK100-2 RSK1/2 S363/S369 Ribosomal S6 protein-serine kinase 1/2 1208 2782 2.62 Q15418 102 NK120-2 p38a (MAPK 14)Pan-specific Mitogen-activated protein-serine kinase p38 alpha 11425 26141 2.63 Q16539 103 PK075-2 PKCb1/2 T500 Protein-serine kinase C beta 1/2 913 2490 3.14 P05771 104 PN030-2 eIF4E S209 Eukaryotic translation initiation factor 4 (mRNA cap binding protein) 500 1531 3.48 P06730 Supplemental Table II: Proteins that are differentially regulated in response to IL-2 in CD151- CD4+ T cells

Antibody Target Phospho Site CD151- Phospho- MAPK Cell Serial No. Full Target Protein Name CD151- Z-ratio Uniprot Link Cell death Codes Protein Name (Human) + IL-2 rylation cascade proliferation

1 174 PN023 CREB1 S129/S133 cAMP response element binding protein 1 3469 233 -2.81 P16220 2 435 PN154 Jun S243 Jun proto-oncogene-encoded AP1 transcription factor 568 51 -2.46 P05412 3 321 PN196 GATA1 S142 Erythroid transcription factor 711 105 -1.96 P15976 4 137 NK026-7 CDK2 Pan-specific Cyclin-dependent protein-serine kinase 2 12506 2560 -1.69 P24941 5 62 NN006-1 BCL Pan-specific B-cell lymphoma protein 2 alpha 975 220 -1.53 P10415 6 242 PN172 eIF4B S422 Eukaryotic translation initiation factor 4B 1722 404 -1.50 P23588 7 3 PN114 4E-BP1 T45 Eukaryotic translation initiation factor 4E binding protein 1 (PHAS1) 1865 486 -1.39 Q13541 8 154 PK162 Chk1 S280 Checkpoint protein-serine kinase 1 3220 875 -1.36 O14757 9 701 PN062 PRAS40 T246 Proline-rich Akt substrate 40 kDa (Akt1S1) 2041 588 -1.29 Q96B36 10 729 PN064 Rad17 S645 Rad17 homolog 1207 343 -1.29 O75943 11 354 NN054 Hsc70 Pan-specific Heat shock 70 kDa protein 8 8558 2595 -1.28 P33778 12 728 PN063 Rac1/cdc42 S71 Ras-related C3 botulinum toxin substrate 1 627 185 -1.24 P63000 13 813 NN105 STAT5A Pan-specific Signal transducer and activator of transcription 5A 21244 7007 -1.21 P42229 14 123 NN023 Cdc34 Pan-specific Cell division cycle 34 (ubiquitin-conjugating ligase) 3224 1037 -1.19 P49427 15 817 NN108 STI1 Pan-specific Stress induced phosphoprotein 1 (Hsc70/Hsp90 organizing protein (Hop)) 1527 481 -1.19 P31948 16 695 NP018 PP2Cd Pan-specific Protein-serine phosphatase 2C - catalytic subunit - delta isoform 1136 364 -1.17 O15297 17 166 PN019 Cofilin 1 S3 Cofilin 1 1603 523 -1.16 P23528 18 513 PK055-1 Met Y1230/Y1234/Y1235Hepatocyte growth factor (HGF) receptor-tyrosine kinase 1384 451 -1.15 P08581 19 428 NK217 JNK1 Pan-specific Jun N-terminus protein-serine kinase (stress-activated protein kinase (SAPK)) 1 1062 350 -1.14 P45983 20 854 PK133 VEGFR2 Y1214 Vascular endothelial growth factor receptor-tyrosine kinase 2 (Flk1) 1321 436 -1.14 P35968 21 47 PN115 ATF2 S94/S112 Activating transcription factor 2 (CRE-BP1) 2146 727 -1.13 P15336 22 725 PK097-3 PYK2 Y579 Protein-tyrosine kinase 2 1538 516 -1.13 Q14289 23 250 PN170 Elk1 S389 ETS domain-containing protein Elk-1 1241 417 -1.12 P19419 24 58 PN009 B23 (NPM) T234/237 B23 (nucleophosmin, numatrin, nucleolar protein NO38) 1682 586 -1.09 P06748 25 610 NK200-2 PAKg Pan-specific p21-activated kinase 2 (gamma) (serine/threonine-protein kinase PAK 2) 11133 4059 -1.09 Q13177 26 760 PK157 RSK1 S352 Ribosomal S6 protein-serine kinase 1 2104 739 -1.09 Q15418 27 434 NN162 Jun Pan-specific Jun proto-oncogene-encoded AP1 transcription factor 1314 460 -1.08 P05412 28 132 PK008-1 CDK1/CDC2 T161 Cyclin-dependent protein-serine kinase 1/2 1167 424 -1.04 P06493 29 606 PK061 PAK1/2/3 S144/S141/S154p21-activated kinase 1 (alpha) (serine/threonine-protein kinase PAK 1) 1177 429 -1.03 Q13153 30 455 PK041 Lck Y505 Lymphocyte-specific protein-tyrosine kinase 2058 786 -1.00 P06239 31 652 NK135 PKCd Pan-specific Protein-serine kinase C delta 6982 12572 1.01 Q05655 32 650 PK075-2 PKCb1/2 T500 Protein-serine kinase C beta 1/2 913 1597 1.04 P05771 33 361 PN041 Hsp27 S78 Heat shock 27 kDa protein beta 1 (HspB1) 13085 24743 1.07 P04792 34 175 PN024 CREB1 S133 cAMP response element binding protein 1 28402 55552 1.09 P16220 35 765 PK101-2 RSK1/2 S380/S386 Ribosomal S6 protein-serine kinase 1/2 1831 3410 1.13 Q15418 36 764 PK100-2 RSK1/2 S363/S369 Ribosomal S6 protein-serine kinase 1/2 1208 2262 1.15 Q15418 37 458 NK227-2 LKB1 Pan-specific Serine/threonine-protein kinase 11 22829 46279 1.17 Q15831 38 93 NK022 CaMKK Pan-specific Calcium/calmodulin-dependent protein-serine kinase kinase 4886 9956 1.24 Q8N5S9 39 78 PN116 BRCA1 S1423 Breast cancer type 1 susceptibility protein 2969 6047 1.27 P38398 40 459 NK227-3 LKB1 Pan-specific Serine/threonine-protein kinase 11 38399 84264 1.29 Q15831 41 203 NP006-2 DUSP1 (MKP1)Pan-specific MAP kinase phosphatase 1 (CL100, VH1) 30957 69448 1.34 P28562 42 763 PK100 RSK1/2 S363/S369 Ribosomal S6 protein-serine kinase 1/2 2153 4525 1.34 Q15418 43 470 NN155 MEF-2 Pan-specific Myelin expression factor 2 (MYEF2) 5073 11024 1.36 Q9P2K5 44 74 NK156-4 B-Raf Pan-specific RafB proto-oncogene-encoded protein-serine kinase 20719 47428 1.39 P15056 45 757 NK163-3 Ros Pan-specific Orosomucoid 1 receptor-tyrosine kinase 26933 62397 1.40 P08922 46 265 NK055-2 ERK1 Pan-specific Extracellular regulated protein-serine kinase 1 (p44 MAP kinase) 37157 88687 1.44 P27361 47 89 NK019-2 CAMK2d Pan-specific Calcium/calmodulin-dependent protein-serine kinase 2 delta 2324 5252 1.46 Q13557 48 364 NN057-3 Hsp40 Pan-specific DnaJ homolog, subfamily B member 1 18087 42856 1.46 P25685 49 852 NN176 VEGF-C Pan-specific Vascular endothelial growth factor C 5256 12440 1.51 P49767 50 847 NK181-4 TYK2 Pan-specific Protein-tyrosine kinase 2 (Jak-related) 27398 68594 1.54 P29597 51 84 PN015 Caldesmon S789 Caldesmon 3777 9038 1.55 Q05682 52 266 NK055-3 ERK1 Pan-specific Extracellular regulated protein-serine kinase 1 (p44 MAP kinase) 37206 94331 1.55 P27361 53 456 NK093 LIMK1 Pan-specific LIM domain kinase 1 4188 10057 1.55 P53667 54 474 NK099-8 MEK1 Pan-specific MAPK/ERK protein-serine kinase 1 (MKK1) 28486 71897 1.55 Q02750 55 846 NK181-3 TYK2 Pan-specific Protein-tyrosine kinase 2 (Jak-related) 30973 79263 1.57 P29597 56 647 PK073 PKCa S657 Protein-serine kinase C alpha 3917 9721 1.61 P17252 57 653 PK079-1 PKCd S645 Protein-serine kinase C delta 2709 6680 1.62 Q05655 58 758 NK163-4 Ros Pan-specific Orosomucoid 1 receptor-tyrosine kinase 26710 71085 1.65 P08922 59 264 NK055-1 ERK1 Pan-specific Extracellular regulated protein-serine kinase 1 (p44 MAP kinase) 31582 88820 1.74 P27361 60 463 PK044 MAPKAPK2 T222 Mitogen-activated protein kinase-activated protein kinase 2 5182 14309 1.79 P49137 61 460 NK227-4 LKB1 Pan-specific Serine/threonine-protein kinase 11 29746 88318 1.84 Q15831 62 187 PN190 Cyclin B1 S147 Cyclin B1 3137 10644 2.19 P14635 63 79 PN014 BRCA1 S1497 Breast cancer type 1 susceptibility protein 6499 24876 2.37 P38398 Supplemental Table III: Proteins that are differentially regulated in response to IL-2 in CD151+ CD4+ T cells

Antibody Target Phospho Site CD151+ Phospho- MAPK Cell Serial No. Full Target Protein Name CD151+ Z-ratio Uniprot Link Cell death Codes Protein Name (Human) +IL-2 rylation cascade proliferation

1 174 PN023 CREB1 S129/S133 cAMP response element binding protein 1 4048 620 -2.63 P16220 2 312 PN195 FKHR S319 Forkhead box protein O1 531 85 -2.54 Q12778 3 245 PN030-2 eIF4E S209 Eukaryotic translation initiation factor 4 (mRNA cap binding protein) 1531 273 -2.41 P06730 4 709 PN104 Progesterone ReceptorS294 Progesterone receptor 623 122 -2.27 P06401 5 137 NK026-7 CDK2 Pan-specific Cyclin-dependent protein-serine kinase 2 13424 3482 -1.93 P24941 6 534 NK111 Mnk2 Pan-specific MAP kinase-interacting protein-serine kinase 2 (calmodulin-activated) 3973 1139 -1.78 Q9HBH9 7 46 PK143 ASK1 S966 Apoptosis signal regulating protein-serine kinase 1 722 206 -1.76 Q59GL6 8 248 NN168 Elk1 Pan-specific ETS domain-containing protein Elk-1 940 269 -1.76 P19419 9 701 PN062 PRAS40 T246 Proline-rich Akt substrate 40 kDa (Akt1S1) 2057 604 -1.74 Q96B36 10 97 NN016 Caspase 6 Pan-specific Caspase 6 (apoptotic protease Mch2) 996 301 -1.69 P55212 11 242 PN172 eIF4B S422 Eukaryotic translation initiation factor 4B 1664 516 -1.66 P23588 12 439 PN155 Jun Y170 Jun proto-oncogene-encoded AP1 transcription factor 1458 455 -1.65 P05412 13 143 NK028-5 CDK5 Pan-specific Cyclin-dependent protein-serine kinase 5 14047 4821 -1.55 Q00535 14 729 PN064 Rad17 S645 Rad17 homolog 1010 348 -1.51 O75943 15 250 PN170 Elk1 S389 ETS domain-containing protein Elk-1 1026 361 -1.49 P19419 16 760 PK157 RSK1 S352 Ribosomal S6 protein-serine kinase 1 1860 682 -1.44 Q15418 17 734 NN093 Rb Pan-specific Retinoblastoma-associated protein 1 1724 633 -1.43 P06400 18 147 NK030-2 CDK7 Pan-specific Cyclin-dependent protein-serine kinase 7 11993 4557 -1.41 P50613 19 3 PN114 4E-BP1 T45 Eukaryotic translation initiation factor 4E binding protein 1 (PHAS1) 771 290 -1.39 Q13541 20 548 PN182 MyoD S200 Myoblast determination protein 1 1038 394 -1.38 P15172 21 606 PK061 PAK1/2/3 S144/S141/S154p21-activated kinase 1 (alpha) (serine/threonine-protein kinase PAK 1) 1211 462 -1.38 Q13153 22 16 NK129 Akt1 (PKBa) Pan-specific RAC-alpha serine/threonine-protein kinase 8129 3229 -1.35 P31749 23 356 NN055 HSF4 Pan-specific Heat shock transcription factor 4 1272 501 -1.33 P84243 24 683 PN144 PLCg1 Y783 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase gamma-1 521 206 -1.32 P19174 25 428 NK217 JNK1 Pan-specific Jun N-terminus protein-serine kinase (stress-activated protein kinase (SAPK)) 1 995 400 -1.30 P45983 26 829 PN107 Tau S422 Microtubule-associated protein tau 2347 996 -1.24 P10636 27 409 PN118 IRS1 S639 Insulin receptor substrate 1 1455 619 -1.23 P35568 28 451 NK092-3 Lck Pan-specific Lymphocyte-specific protein-tyrosine kinase 985 421 -1.22 P06239 29 183 NK044 Csk Pan-specific C-terminus of Src tyrosine kinase 2111 911 -1.22 P41240 30 860 NP030 VHR Pan-specific Dual specificity protein phosphatase 3 1452 626 -1.21 P51452 31 62 NN006-1 BCL Pan-specific B-cell lymphoma protein 2 alpha 456 195 -1.21 P10415 32 354 NN054 Hsc70 Pan-specific Heat shock 70 kDa protein 8 8901 3934 -1.20 P33778 33 63 NN006 Bcl2 Pan-specific B-cell lymphoma protein 2 alpha 1830 803 -1.19 P10415 34 560 NK207 NIK Pan-specific NF-kappa beta-inducing kinase 6037 2726 -1.17 Q99558 35 435 PN154 Jun S243 Jun proto-oncogene-encoded AP1 transcription factor 567 252 -1.16 P05412 36 193 PN026 Dab1 Y198 Disabled homolog 1 2018 925 -1.13 O75553 37 824 NK175-5 TAK1 Pan-specific TGF-beta-activated protein-serine kinase 1 10455 4977 -1.10 O43318 38 126 NK025-1 CDK1 Pan-specific Cyclin-dependent protein-serine kinase 1 30090 14525 -1.10 P06493 39 321 PN196 GATA1 S142 Erythroid transcription factor 606 284 -1.09 P15976 40 497 NK104 MEK5 Pan-specific MAPK/ERK protein-serine kinase 5 (MKK5) 4343 2083 -1.08 Q13163 41 538 NK113-2 MST1 Pan-specific Mammalian STE20-like protein-serine kinase 1 (KRS2) 949 451 -1.08 Q13043 42 7 NK001 Abl Pan-specific Abelson proto-oncogene-encoded protein-tyrosine kinase 1663 806 -1.05 P00519 43 311 PN194 FKHR S256 Forkhead box protein O1 707 340 -1.05 Q12778 44 681 PK132 PKR1 T446 Double-stranded RNA-dependent protein-serine kinase 780 382 -1.03 P19525 45 871 NK186-2 Yes Pan-specific Yamaguchi sarcoma proto-oncogene-encoded tyrosine kinase 379 185 -1.03 P07947 46 632 NN181-1 PDK3 Pan-specific Pyruvate dehydrogenase kinase isoform 3 1968 975 -1.03 Q15120 47 766 PK102 RSK1/2/3 T573 Ribosomal S6 protein-serine kinase 1/2/3 560 276 -1.02 Q15418 48 430 NK088-2 JNK2 Pan-specific Jun N-terminus protein-serine kinase (stress-activated protein kinase (SAPK)) 1 8767 4451 -1.01 P45983 49 166 PN019 Cofilin 1 S3 Cofilin 1 1748 879 -1.01 P23528 50 92 NK211 CamKI Pan-specific Calcium/calmodulin-dependent protein-serine kinase 1 alpha 5566 2848 -1.00 Q14012 51 868 NK254-1 WNK3 Pan-specific Serine/threonine-protein kinase WNK3 28779 49415 1.02 Q9BYP7 52 532 NN132 mMOB1 Pan-specific Preimplantation protein 3 24995 42906 1.02 Q9Y3A3 53 259 NK231-2 ErbB3 Pan-specific Tyrosine kinase-type cell surface receptor HER3 38191 66123 1.03 P21860 54 544 NK116-4 mTOR Pan-specific Mammalian target of rapamycin (FRAP) 30321 52429 1.03 P42345 55 255 NK054-4 ErbB2 Pan-specific ErbB2 (Neu) receptor-tyrosine kinase 46335 80475 1.03 P04626 56 466 PN050-1 MARCKS S152/S156 Myristoylated alanine-rich protein kinase C substrate 639 1068 1.03 P29966 57 358 NN152-1 Hsp25 Pan-specific Heat shock 27 kDa protein beta 1 (HspB1) 24508 42718 1.05 P84243 58 771 PN161 Shc1 Y349 SH2 domain-containing transforming protein 1 319 536 1.06 P29353 59 763 PK100 RSK1/2 S363/S369 Ribosomal S6 protein-serine kinase 1/2 2402 4119 1.06 Q15418 60 678 NK203 PKG1b-NT Pan-specific cGMP-dependent protein kinase 1, beta isozyme 3440 5927 1.07 P14619 61 836 PK829 TEC Y519 Tyrosine-protein kinase Tec 23469 41664 1.09 P42680 62 525 NK105-5 MKK6 Pan-specific MAPK/ERK protein-serine kinase 6 (MKK6) 27201 48394 1.10 P52564 63 706 NK048-6 PRKDC (DNAPK)Pan-specific DNA-activated protein-serine kinase 33582 60844 1.13 P78527 64 301 NK061 Fes Pan-specific Fes/Fps protein-tyrosine kinase 3149 5586 1.13 P07332 65 167 PN020 Cofilin 2 S3 Cofilin 2 9922 17790 1.13 Q9Y281 66 758 NK163-4 Ros Pan-specific Orosomucoid 1 receptor-tyrosine kinase 31552 57335 1.14 P08922 67 855 NK226-2 VGFR1 Pan-specific Vascular endothelial growth factor receptor 1 36700 66862 1.14 P17948 68 332 NN049 Grp94 Pan-specific Glucose regulated protein 94 (endoplasmin) 31855 58268 1.15 P14625 69 520 NK103-4 MKK4 Pan-specific MAPK/ERK protein-serine kinase 4 (MKK4) 29498 54033 1.16 P45985 70 786 PN125 SMC1 S957 Structural maintenance of chromosomes protein 1A 11481 20862 1.16 Q14683 71 577 PK739 p38a MAPK T180+pY182 Mitogen-activated protein-serine kinase p38 alpha 5450 9842 1.16 Q16539 72 442 NK241-2 Kit Pan-specific Mast/stem cell growth factor receptor Kit 29913 55164 1.17 P10721 73 298 PK629 FAK Y577 Focal adhesion protein-tyrosine kinase 3241 5914 1.19 Q05397 74 633 NN181-2 PDK3 Pan-specific Pyruvate dehydrogenase kinase isoform 3 30625 57664 1.22 Q15120 75 799 NK172-2 Src Pan-specific Src proto-oncogene-encoded protein-tyrosine kinase 26954 50923 1.23 P12931 76 847 NK181-4 TYK2 Pan-specific Protein-tyrosine kinase 2 (Jak-related) 43928 84730 1.26 P29597 77 699 NP021 PP5/PPT Pan-specific Protein-serine phosphatase 5 - catalytic subunit (PPT) 388 716 1.26 P53041 78 83 NN174 CA9 Pan-specific Carbonic anhydrase 9 5178 9838 1.27 Q16790 79 277 NK056-4 ERK2 Pan-specific Extracellular regulated protein-serine kinase 2 (p42 MAP kinase) 32595 63025 1.27 P28482 80 757 NK163-3 Ros Pan-specific Orosomucoid 1 receptor-tyrosine kinase 29192 56437 1.28 P08922 81 458 NK227-2 LKB1 Pan-specific Serine/threonine-protein kinase 11 35307 68527 1.28 Q15831 82 368 NN059-3 Hsp60 Pan-specific Heat shock 60 kDa protein 1 (chaperonin, CPN60) 9800 18844 1.29 P10809 83 563 PN054 NMDAR2B Y1472 N-methyl-D-aspartate (NMDA) glutamate receptor 2B subunit 586 1106 1.30 Q13224 84 302 NK062-3 FGFR1 Pan-specific Fibroblast growth factor receptor-tyrosine kinase 1 28267 55439 1.31 P11362 85 718 NP024 PTP1B Pan-specific Protein-tyrosine phosphatase 1B 912 1748 1.33 P18031 86 647 PK073 PKCa S657 Protein-serine kinase C alpha 7650 15060 1.34 P17252 87 474 NK099-8 MEK1 Pan-specific MAPK/ERK protein-serine kinase 1 (MKK1) 40417 80986 1.35 Q02750 88 835 PK828 TBK1 S172 Serine/threonine-protein kinase TBK1 30807 62174 1.37 Q9UHD2 89 524 NK105-4 MKK6 Pan-specific MAPK/ERK protein-serine kinase 6 (MKK6) 23036 46473 1.37 P52564 90 395 PK154 IKKa T23 Inhibitor of NF-kappa-B protein-serine kinase alpha (CHUK) 864 1698 1.38 O15111 91 331 NN048-2 Grp78 Pan-specific Glucose regulated protein 78 22110 44787 1.38 P11021 92 113 NP038-1 Cdc25A Pan-specific Cell division cycle 25A phosphatase 26893 54702 1.39 P30304 93 473 NK099-7 MEK1 Pan-specific MAPK/ERK protein-serine kinase 1 (MKK1) 33131 68328 1.42 Q02750 94 39 NK205-4 A-Raf Pan-specific A-Raf proto-oncogene serine/threonine-protein kinase 42433 87803 1.42 P10398 95 421 NK086-2 JAK3 Pan-specific Janus protein-tyrosine kinase 3 29661 61255 1.42 P52333 96 265 NK055-2 ERK1 Pan-specific Extracellular regulated protein-serine kinase 1 (p44 MAP kinase) 38943 80624 1.42 P27361 97 521 NK103-5 MKK4 Pan-specific MAPK/ERK protein-serine kinase 4 (MKK4) 31722 65589 1.42 P45985 98 273 NK055-NK056-2ERK1/2 Pan-specific Extracellular regulated protein-serine kinase 1 (p44 MAP kinase) + Extracellular regulated28097 protein-serine58082 kinase 2 (p421.42 MAP kinase) P27361 99 275 PK168-PK169 ERK1/2 Y204+Y187 Extracellular regulated protein-serine kinase 1 (p44 MAP kinase) + Extracellular regulated3650 protein-serine7407 kinase 2 (p421.42 MAP kinase) P27361 100 266 NK055-3 ERK1 Pan-specific Extracellular regulated protein-serine kinase 1 (p44 MAP kinase) 40478 84042 1.43 P27361 101 460 NK227-4 LKB1 Pan-specific Serine/threonine-protein kinase 11 32026 71557 1.59 Q15831 102 865 NK252-1 WNK1 Pan-specific Serine/threonine-protein kinase WNK1 29843 70659 1.72 Q9H4A3 103 586 NK059-1 p38g MAPK Pan-specific Mitogen-activated protein-serine kinase p38 gamma (MAPK12) 6862 16293 1.76 P53778 104 74 NK156-4 B-Raf Pan-specific RafB proto-oncogene-encoded protein-serine kinase 25702 62781 1.79 P15056 105 463 PK044 MAPKAPK2 T222 Mitogen-activated protein kinase-activated protein kinase 2 4498 11048 1.84 P49137 106 377 NN063 HspBP1 Pan-specific Hsp70 binding protein 1 4279 11476 2.03 O95351 107 669 PK087 PKCl T555/T563 Protein-serine kinase C lambda/iota 1091 2922 2.06 P41743 108 187 PN190 Cyclin B1 S147 Cyclin B1 3702 10138 2.08 P14635 108 456 NK093 LIMK1 Pan-specific LIM domain kinase 1 3537 10571 2.27 P53667 109 79 PN014 BRCA1 S1497 Breast cancer type 1 susceptibility protein 6507 20313 2.36 P38398 110 802 PK107 Src Y418 Src proto-oncogene-encoded protein-tyrosine kinase 754 2711 2.71 P12931 Supplemental Table IV: Altered proteins that are shared by CD151- and CD151+ CD4+ T cells in response to IL-2 stimulation

Antibody Target Phospho Site CD151- CD151+ Serial No. Full Target Protein Name CD151- Z-ratio CD151+ Z-ratio Uniprot Link Codes Protein Name (Human) + IL-2 +IL-2

1 174 PN023 CREB1 S129/S133 cAMP response element binding protein 1 3469 233 -2.81 4048 620 -2.63 P16220 2 435 PN154 Jun S243 Jun proto-oncogene-encoded AP1 transcription factor 568 51 -2.46 567 252 -1.16 P05412 3 321 PN196 GATA1 S142 Erythroid transcription factor 711 105 -1.96 606 284 -1.09 P15976 4 62 NN006-1 BCL Pan-specific B-cell lymphoma protein 2 alpha 975 220 -1.53 456 195 -1.21 P10415 5 242 PN172 eIF4B S422 Eukaryotic translation initiation factor 4B 1722 404 -1.50 1664 516 -1.66 P23588 6 3 PN114 4E-BP1 T45 Eukaryotic translation initiation factor 4E binding protein 1 (PHAS1) 1865 486 -1.39 771 290 -1.39 Q13541 7 701 PN062 PRAS40 T246 Proline-rich Akt substrate 40 kDa (Akt1S1) 2041 588 -1.29 2057 604 -1.74 Q96B36 8 729 PN064 Rad17 S645 Rad17 homolog 1207 343 -1.29 1010 348 -1.51 O75943 9 354 NN054 Hsc70 Pan-specific Heat shock 70 kDa protein 8 8558 2595 -1.28 8901 3934 -1.20 P33778 10 166 PN019 Cofilin 1 S3 Cofilin 1 1603 523 -1.16 1748 879 -1.01 P23528 11 428 NK217 JNK1 Pan-specific Jun N-terminus protein-serine kinase (stress-activated protein kinase (SAPK)) 1 1062 350 -1.14 995 400 -1.30 P45983 12 250 PN170 Elk1 S389 ETS domain-containing protein Elk-1 1241 417 -1.12 1026 361 -1.49 P19419 13 760 PK157 RSK1 S352 Ribosomal S6 protein-serine kinase 1 2104 739 -1.09 1860 682 -1.44 Q15418 14 606 PK061 PAK1/2/3 S144/S141/S154p21-activated kinase 1 (alpha) (serine/threonine-protein kinase PAK 1) 1177 429 -1.03 1211 462 -1.38 Q13153 15 458 NK227-2 LKB1 Pan-specific Serine/threonine-protein kinase 11 22829 46279 1.17 35307 68527 1.28 Q15831 16 763 PK100 RSK1/2 S363/S369 Ribosomal S6 protein-serine kinase 1/2 2153 4525 1.34 2402 4119 1.06 Q15418 17 74 NK156-4 B-Raf Pan-specific RafB proto-oncogene-encoded protein-serine kinase 20719 47428 1.39 25702 62781 1.79 P15056 18 757 NK163-3 Ros Pan-specific Orosomucoid 1 receptor-tyrosine kinase 26933 62397 1.40 29192 56437 1.28 P08922 19 265 NK055-2 ERK1 Pan-specific Extracellular regulated protein-serine kinase 1 (p44 MAP kinase) 37157 88687 1.44 38943 80624 1.42 P27361 20 847 NK181-4 TYK2 Pan-specific Protein-tyrosine kinase 2 (Jak-related) 27398 68594 1.54 43928 84730 1.26 P29597 21 266 NK055-3 ERK1 Pan-specific Extracellular regulated protein-serine kinase 1 (p44 MAP kinase) 37206 94331 1.55 40478 84042 1.43 P27361 22 456 NK093 LIMK1 Pan-specific LIM domain kinase 1 4188 10057 1.55 3537 10571 2.27 P53667 23 474 NK099-8 MEK1 Pan-specific MAPK/ERK protein-serine kinase 1 (MKK1) 28486 71897 1.55 40417 80986 1.35 Q02750 24 758 NK163-4 Ros Pan-specific Orosomucoid 1 receptor-tyrosine kinase 26710 71085 1.65 31552 57335 1.14 P08922 25 463 PK044 MAPKAPK2 T222 Mitogen-activated protein kinase-activated protein kinase 2 5182 14309 1.79 4498 11048 1.84 P49137 26 460 NK227-4 LKB1 Pan-specific Serine/threonine-protein kinase 11 29746 88318 1.84 32026 71557 1.59 Q15831 27 187 PN190 Cyclin B1 S147 Cyclin B1 3137 10644 2.19 3702 10138 2.08 P14635 28 79 PN014 BRCA1 S1497 Breast cancer type 1 susceptibility protein 6499 24876 2.37 6507 20313 2.36 P38398 Supplemental Table V: Proteins that are specifically altered in CD151- CD4+ T cells in response to IL-2 stimulation.

Antibody Target Phospho Site CD151- Serial No. Full Target Protein Name CD151- Z-ratio Uniprot Link Codes Protein Name (Human) + IL-2

1 137 NK026-7 CDK2 Pan-specific Cyclin-dependent protein-serine kinase 2 12506 2560 -1.69 P24941 2 154 PK162 Chk1 S280 Checkpoint protein-serine kinase 1 3220 875 -1.36 O14757 3 728 PN063 Rac1/cdc42 S71 Ras-related C3 botulinum toxin substrate 1 627 185 -1.24 P63000 4 813 NN105 STAT5A Pan-specific Signal transducer and activator of transcription 5A 21244 7007 -1.21 P42229 5 123 NN023 Cdc34 Pan-specific Cell division cycle 34 (ubiquitin-conjugating ligase) 3224 1037 -1.19 P49427 6 817 NN108 STI1 Pan-specific Stress induced phosphoprotein 1 (Hsc70/Hsp90 organizing protein (Hop)) 1527 481 -1.19 P31948 7 695 NP018 PP2Cd Pan-specific Protein-serine phosphatase 2C - catalytic subunit - delta isoform 1136 364 -1.17 O15297 8 513 PK055-1 Met Y1230/Y1234/Y1235Hepatocyte growth factor (HGF) receptor-tyrosine kinase 1384 451 -1.15 P08581 9 854 PK133 VEGFR2 Y1214 Vascular endothelial growth factor receptor-tyrosine kinase 2 (Flk1) 1321 436 -1.14 P35968 10 47 PN115 ATF2 S94/S112 Activating transcription factor 2 (CRE-BP1) 2146 727 -1.13 P15336 11 725 PK097-3 PYK2 Y579 Protein-tyrosine kinase 2 1538 516 -1.13 Q14289 12 58 PN009 B23 (NPM) T234/237 B23 (nucleophosmin, numatrin, nucleolar protein NO38) 1682 586 -1.09 P06748 13 610 NK200-2 PAKg Pan-specific p21-activated kinase 2 (gamma) (serine/threonine-protein kinase PAK 2) 11133 4059 -1.09 Q13177 14 132 PK008-1 CDK1/CDC2 T161 Cyclin-dependent protein-serine kinase 1/2 1167 424 -1.04 P06493 15 455 PK041 Lck Y505 Lymphocyte-specific protein-tyrosine kinase 2058 786 -1.00 P06239 16 652 NK135 PKCd Pan-specific Protein-serine kinase C delta 6982 12572 1.01 Q05655 17 650 PK075-2 PKCb1/2 T500 Protein-serine kinase C beta 1/2 913 1597 1.04 P05771 18 361 PN041 Hsp27 S78 Heat shock 27 kDa protein beta 1 (HspB1) 13085 24743 1.07 P04792 19 175 PN024 CREB1 S133 cAMP response element binding protein 1 28402 55552 1.09 P16220 20 765 PK101-2 RSK1/2 S380/S386 Ribosomal S6 protein-serine kinase 1/2 1831 3410 1.13 Q15418 21 764 PK100-2 RSK1/2 S363/S369 Ribosomal S6 protein-serine kinase 1/2 1208 2262 1.15 Q15418 22 93 NK022 CaMKK Pan-specific Calcium/calmodulin-dependent protein-serine kinase kinase 4886 9956 1.24 Q8N5S9 23 203 NP006-2 DUSP1 (MKP1)Pan-specific MAP kinase phosphatase 1 (CL100, VH1) 30957 69448 1.34 P28562 24 89 NK019-2 CAMK2d Pan-specific Calcium/calmodulin-dependent protein-serine kinase 2 delta 2324 5252 1.46 Q13557 25 364 NN057-3 Hsp40 Pan-specific DnaJ homolog, subfamily B member 1 18087 42856 1.46 P25685 26 852 NN176 VEGF-C Pan-specific Vascular endothelial growth factor C 5256 12440 1.51 P49767 27 84 PN015 Caldesmon S789 Caldesmon 3777 9038 1.55 Q05682 28 647 PK073 PKCa S657 Protein-serine kinase C alpha 3917 9721 1.61 P17252 29 653 PK079-1 PKCd S645 Protein-serine kinase C delta 2709 6680 1.62 Q05655 Supplemental Table VI: Proteins that are specifically altered in CD151+ CD4+ T cells in response to IL-2 stimulation

Antibody Target Phospho Site CD151+ Serial No. Full Target Protein Name CD151+ Z-ratio Uniprot Link Codes Protein Name (Human) +IL-2

1 312 PN195 FKHR S319 Forkhead box protein O1 531 85 -2.54 Q12778 2 245 PN030-2 eIF4E S209 Eukaryotic translation initiation factor 4 (mRNA cap binding protein) 1531 273 -2.41 P06730 3 709 PN104 Progesterone ReceptorS294 Progesterone receptor 623 122 -2.27 P06401 4 137 NK026-7 CDK2 Pan-specific Cyclin-dependent protein-serine kinase 2 13424 3482 -1.93 P24941 5 534 NK111 Mnk2 Pan-specific MAP kinase-interacting protein-serine kinase 2 (calmodulin-activated) 3973 1139 -1.78 Q9HBH9 6 46 PK143 ASK1 S966 Apoptosis signal regulating protein-serine kinase 1 722 206 -1.76 Q59GL6 7 248 NN168 Elk1 Pan-specific ETS domain-containing protein Elk-1 940 269 -1.76 P19419 8 97 NN016 Caspase 6 Pan-specific Caspase 6 (apoptotic protease Mch2) 996 301 -1.69 P55212 9 439 PN155 Jun Y170 Jun proto-oncogene-encoded AP1 transcription factor 1458 455 -1.65 P05412 10 143 NK028-5 CDK5 Pan-specific Cyclin-dependent protein-serine kinase 5 14047 4821 -1.55 Q00535 11 147 NK030-2 CDK7 Pan-specific Cyclin-dependent protein-serine kinase 7 11993 4557 -1.41 P50613 12 548 PN182 MyoD S200 Myoblast determination protein 1 1038 394 -1.38 P15172 13 16 NK129 Akt1 (PKBa) Pan-specific RAC-alpha serine/threonine-protein kinase 8129 3229 -1.35 P31749 14 356 NN055 HSF4 Pan-specific Heat shock transcription factor 4 1272 501 -1.33 P84243 15 683 PN144 PLCg1 Y783 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase gamma-1 521 206 -1.32 P19174 16 829 PN107 Tau S422 Microtubule-associated protein tau 2347 996 -1.24 P10636 17 409 PN118 IRS1 S639 Insulin receptor substrate 1 1455 619 -1.23 P35568 18 451 NK092-3 Lck Pan-specific Lymphocyte-specific protein-tyrosine kinase 985 421 -1.22 P06239 19 183 NK044 Csk Pan-specific C-terminus of Src tyrosine kinase 2111 911 -1.22 P41240 20 860 NP030 VHR Pan-specific Dual specificity protein phosphatase 3 1452 626 -1.21 P51452 21 63 NN006 Bcl2 Pan-specific B-cell lymphoma protein 2 alpha 1830 803 -1.19 P10415 22 560 NK207 NIK Pan-specific NF-kappa beta-inducing kinase 6037 2726 -1.17 Q99558 23 193 PN026 Dab1 Y198 Disabled homolog 1 2018 925 -1.13 O75553 24 824 NK175-5 TAK1 Pan-specific TGF-beta-activated protein-serine kinase 1 10455 4977 -1.10 O43318 25 126 NK025-1 CDK1 Pan-specific Cyclin-dependent protein-serine kinase 1 30090 14525 -1.10 P06493 26 497 NK104 MEK5 Pan-specific MAPK/ERK protein-serine kinase 5 (MKK5) 4343 2083 -1.08 Q13163 27 538 NK113-2 MST1 Pan-specific Mammalian STE20-like protein-serine kinase 1 (KRS2) 949 451 -1.08 Q13043 28 7 NK001 Abl Pan-specific Abelson proto-oncogene-encoded protein-tyrosine kinase 1663 806 -1.05 P00519 29 311 PN194 FKHR S256 Forkhead box protein O1 707 340 -1.05 Q12778 30 681 PK132 PKR1 T446 Double-stranded RNA-dependent protein-serine kinase 780 382 -1.03 P19525 31 871 NK186-2 Yes Pan-specific Yamaguchi sarcoma proto-oncogene-encoded tyrosine kinase 379 185 -1.03 P07947 32 632 NN181-1 PDK3 Pan-specific Pyruvate dehydrogenase kinase isoform 3 1968 975 -1.03 Q15120 33 766 PK102 RSK1/2/3 T573 Ribosomal S6 protein-serine kinase 1/2/3 560 276 -1.02 Q15418 34 430 NK088-2 JNK2 Pan-specific Jun N-terminus protein-serine kinase (stress-activated protein kinase (SAPK)) 1 8767 4451 -1.01 P45983 35 92 NK211 CamKI Pan-specific Calcium/calmodulin-dependent protein-serine kinase 1 alpha 5566 2848 -1.00 Q14012 36 868 NK254-1 WNK3 Pan-specific Serine/threonine-protein kinase WNK3 28779 49415 1.02 Q9BYP7 37 532 NN132 mMOB1 Pan-specific Preimplantation protein 3 24995 42906 1.02 Q9Y3A3 38 259 NK231-2 ErbB3 Pan-specific Tyrosine kinase-type cell surface receptor HER3 38191 66123 1.03 P21860 39 544 NK116-4 mTOR Pan-specific Mammalian target of rapamycin (FRAP) 30321 52429 1.03 P42345 40 255 NK054-4 ErbB2 Pan-specific ErbB2 (Neu) receptor-tyrosine kinase 46335 80475 1.03 P04626 41 466 PN050-1 MARCKS S152/S156 Myristoylated alanine-rich protein kinase C substrate 639 1068 1.03 P29966 42 358 NN152-1 Hsp25 Pan-specific Heat shock 27 kDa protein beta 1 (HspB1) 24508 42718 1.05 P84243 43 771 PN161 Shc1 Y349 SH2 domain-containing transforming protein 1 319 536 1.06 P29353 44 678 NK203 PKG1b-NT Pan-specific cGMP-dependent protein kinase 1, beta isozyme 3440 5927 1.07 P14619 45 836 PK829 TEC Y519 Tyrosine-protein kinase Tec 23469 41664 1.09 P42680 46 525 NK105-5 MKK6 Pan-specific MAPK/ERK protein-serine kinase 6 (MKK6) 27201 48394 1.10 P52564 47 706 NK048-6 PRKDC (DNAPK)Pan-specific DNA-activated protein-serine kinase 33582 60844 1.13 P78527 48 301 NK061 Fes Pan-specific Fes/Fps protein-tyrosine kinase 3149 5586 1.13 P07332 49 167 PN020 Cofilin 2 S3 Cofilin 2 9922 17790 1.13 Q9Y281 50 855 NK226-2 VGFR1 Pan-specific Vascular endothelial growth factor receptor 1 36700 66862 1.14 P17948 51 332 NN049 Grp94 Pan-specific Glucose regulated protein 94 (endoplasmin) 31855 58268 1.15 P14625 52 520 NK103-4 MKK4 Pan-specific MAPK/ERK protein-serine kinase 4 (MKK4) 29498 54033 1.16 P45985 53 786 PN125 SMC1 S957 Structural maintenance of chromosomes protein 1A 11481 20862 1.16 Q14683 54 577 PK739 p38a MAPK T180+pY182 Mitogen-activated protein-serine kinase p38 alpha 5450 9842 1.16 Q16539 55 442 NK241-2 Kit Pan-specific Mast/stem cell growth factor receptor Kit 29913 55164 1.17 P10721 56 298 PK629 FAK Y577 Focal adhesion protein-tyrosine kinase 3241 5914 1.19 Q05397 57 633 NN181-2 PDK3 Pan-specific Pyruvate dehydrogenase kinase isoform 3 30625 57664 1.22 Q15120 58 799 NK172-2 Src Pan-specific Src proto-oncogene-encoded protein-tyrosine kinase 26954 50923 1.23 P12931 59 699 NP021 PP5/PPT Pan-specific Protein-serine phosphatase 5 - catalytic subunit (PPT) 388 716 1.26 P53041 60 83 NN174 CA9 Pan-specific Carbonic anhydrase 9 5178 9838 1.27 Q16790 61 277 NK056-4 ERK2 Pan-specific Extracellular regulated protein-serine kinase 2 (p42 MAP kinase) 32595 63025 1.27 P28482 62 368 NN059-3 Hsp60 Pan-specific Heat shock 60 kDa protein 1 (chaperonin, CPN60) 9800 18844 1.29 P10809 63 563 PN054 NMDAR2B Y1472 N-methyl-D-aspartate (NMDA) glutamate receptor 2B subunit 586 1106 1.30 Q13224 64 302 NK062-3 FGFR1 Pan-specific Fibroblast growth factor receptor-tyrosine kinase 1 28267 55439 1.31 P11362 65 718 NP024 PTP1B Pan-specific Protein-tyrosine phosphatase 1B 912 1748 1.33 P18031 66 647 PK073 PKCa S657 Protein-serine kinase C alpha 7650 15060 1.34 P17252 67 835 PK828 TBK1 S172 Serine/threonine-protein kinase TBK1 30807 62174 1.37 Q9UHD2 68 524 NK105-4 MKK6 Pan-specific MAPK/ERK protein-serine kinase 6 (MKK6) 23036 46473 1.37 P52564 69 395 PK154 IKKa T23 Inhibitor of NF-kappa-B protein-serine kinase alpha (CHUK) 864 1698 1.38 O15111 70 331 NN048-2 Grp78 Pan-specific Glucose regulated protein 78 22110 44787 1.38 P11021 71 113 NP038-1 Cdc25A Pan-specific Cell division cycle 25A phosphatase 26893 54702 1.39 P30304 72 473 NK099-7 MEK1 Pan-specific MAPK/ERK protein-serine kinase 1 (MKK1) 33131 68328 1.42 Q02750 73 39 NK205-4 A-Raf Pan-specific A-Raf proto-oncogene serine/threonine-protein kinase 42433 87803 1.42 P10398 74 521 NK103-5 MKK4 Pan-specific MAPK/ERK protein-serine kinase 4 (MKK4) 31722 65589 1.42 P45985 75 273 NK055-NK056-2ERK1/2 Pan-specific Extracellular regulated protein-serine kinase 1 (p44 MAP kinase) + Extracellular regulated28097 protein-serine58082 kinase 2 (p421.42 MAP kinase) P27361 76 275 PK168-PK169 ERK1/2 Y204+Y187 Extracellular regulated protein-serine kinase 1 (p44 MAP kinase) + Extracellular regulated3650 protein-serine7407 kinase 2 (p421.42 MAP kinase) P27361 77 865 NK252-1 WNK1 Pan-specific Serine/threonine-protein kinase WNK1 29843 70659 1.72 Q9H4A3 78 586 NK059-1 p38g MAPK Pan-specific Mitogen-activated protein-serine kinase p38 gamma (MAPK12) 6862 16293 1.76 P53778 79 377 NN063 HspBP1 Pan-specific Hsp70 binding protein 1 4279 11476 2.03 O95351 80 669 PK087 PKCl T555/T563 Protein-serine kinase C lambda/iota 1091 2922 2.06 P41743 81 802 PK107 Src Y418 Src proto-oncogene-encoded protein-tyrosine kinase 754 2711 2.71 P12931 Supplemental Table VII: Proteins that are altered in Jurkat T cells by CD151 overexpression.

Target Phospho Site Phospho- MAPK Cell Full Target Protein Name Jurkat J-CD151 Z-ratio Uniprot Link Cell death Protein Name (Human) rylation cascade proliferation

1 NFKB p65 S529 NF-kappa-B p65 nuclear transcription factor 879 1791 1.00 Q04206 2 Yes Pan-specific Yamaguchi sarcoma proto-oncogene-encoded tyrosine kinase 813 1698 1.04 P07947 3 Hsp60 Pan-specific Heat shock 60 kDa protein 1 (chaperonin, CPN60) 1896 4145 1.05 P10809 4 Myc S373 Myc proto-oncogene protein 1118 2419 1.07 P01106 5 Cofilin Pan-specific Cofilin 1 1103 2385 1.07 P23528 6 eIF2a Pan-specific Eukaryotic translation initiation factor 2 alpha 1073 2332 1.08 P05198 7 PTP1C Pan-specific Protein-tyrosine phosphatase 1C (SHP1, SHPTP1) 1347 2982 1.09 P29350 8 GluR1 S849 Glutamate receptor 1 2235 5067 1.09 P42261 9 PP2Cd Pan-specific Protein-serine phosphatase 2C - catalytic subunit - delta isoform 987 2166 1.09 O15297 10 PTEN S380/T382/T383Phosphatidylinositol-3,4,5-trisphosphate 3-phosphatase and protein phosphatase and tensin1195 homolog deleted2674 on chromosome1.11 10 P60484 11 Histone H2A.X S139 Histone H2A variant X 622 1356 1.11 P16104 12 CDK1/2 Y15 Cyclin-dependent protein-serine kinase 1/2 711 1568 1.12 P06493 13 c-Cbl Y700 Signal transduction protein CBL 853 1897 1.12 P22681 14 Gab1 Y627 GRB2-associated binder 1 648 1453 1.15 Q13480 15 MKP2 Pan-specific MAP kinase phosphatase 2 (VH2) 855 1943 1.15 Q13115 16 PSD-95 Pan-specific Disks large homolog 4 836 1988 1.22 P78352 17 eIF4E S209 Eukaryotic translation initiation factor 4 (mRNA cap binding protein) 1116 2696 1.22 P06730 18 PKR1 T446 Double-stranded RNA-dependent protein-serine kinase 1161 2811 1.22 P19525 19 PLCg2 Y753 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase gamma-2 1181 2875 1.23 P16885 20 CDK1/CDC2 T161 Cyclin-dependent protein-serine kinase 1/2 547 1303 1.24 P06493 21 Akt1 (PKBa) S473 RAC-alpha serine/threonine-protein kinase 2076 5250 1.25 P31749 22 GNB2L1 Pan-specific Guanine nucleotide-binding protein beta (receptor for activated C kinase 1 (RACK1)) 1923 4880 1.26 P63244 23 RIP2/RICK Pan-specific Receptor-interacting serine/threonine-protein kinase 2 (RIPK2) 1123 2803 1.26 O43353 24 HDAC4/5/9 S246/259/220 Histone deacetylase 4 980 2616 1.36 P56524 25 MyoD S200 Myoblast determination protein 1 665 1805 1.41 P15172 26 LAR Pan-specific LCA antigen-related (LAR) receptor tyrosine phosphatase 624 1695 1.42 P10586 27 Caspase 7 Pan-specific Caspase 7 (ICE-like apoptotic protease 3 (ICE-LAP3), Mch3) 1797 5136 1.42 P55210 28 PKA R2a (PKR2) S98 cAMP-dependent protein-serine kinase regulatory type 2 subunit alpha 1183 3419 1.46 P13861 29 MYPT1 T696 Myosin phosphatase target 1 1259 3694 1.48 O14974 30 IRS1 S312 Insulin receptor substrate 1 963 2930 1.55 P35568 31 Tau T205 Microtubule-associated protein tau 909 2887 1.61 P10636 32 p70 S6K S424 Ribosomal protein S6 kinase beta-1 974 3240 1.67 P23443 33 Shc1 Y349 SH2 domain-containing transforming protein 1 556 1818 1.68 P29353 34 MEK6 Pan-specific MAPK/ERK protein-serine kinase 6 (MKK6) 311 1076 1.79 P52564 35 FKHR S319 Forkhead box protein O1 406 1430 1.80 Q12778 36 IKKa T23 Inhibitor of NF-kappa-B protein-serine kinase alpha (CHUK) 898 3273 1.80 O15111 37 Rb S780 Retinoblastoma-associated protein 1 586 2124 1.82 P06400 38 S6 S235 40S ribosomal protein S6 1639 6498 1.88 P62753 39 4E-BP1 Pan-specific Eukaryotic translation initiation factor 4E binding protein 1 (PHAS1) 1150 4501 1.88 Q13541 40 IRS1 S639 Insulin receptor substrate 1 620 2365 1.88 P35568 41 4E-BP1 T45 Eukaryotic translation initiation factor 4E binding protein 1 (PHAS1) 949 3731 1.90 Q13541 42 STAT2 Y689 Signal transducer and activator of transcription 2 504 1997 1.95 P52630 43 Catenin a S641 Catenin (cadherin-associated protein) alpha 663 2691 1.97 P35221 44 PLCg1 Y783 1-phosphatidylinositol-4,5-bisphosphate phosphodiesterase gamma-1 747 3132 2.00 P19174 45 JAK1 Y1022 Janus protein-tyrosine kinase 1 582 2565 2.09 P23458 46 EGFR Y1197 Epidermal growth factor receptor-tyrosine kinase 712 3642 2.28 P00533 47 BCL Pan-specific B-cell lymphoma protein 2 alpha 195 1384 2.80 P10415