Cancer‐associated mutations in VAV1 trigger variegated signaling outputs and T‐cell lymphomagenesis
2021; Springer Nature; Volume: 40; Issue: 22 Linguagem: Inglês
10.15252/embj.2021108125
ISSN1460-2075
AutoresJavier Robles‐Valero, Lucía Fernández‐Nevado, L. Francisco Lorenzo‐Martín, Myriam Cuadrado, Isabel Fernández‐Pisonero, Sonia Rodríguez‐Fdez, Elsa N. Astorga‐Simón, Antonio Abad, Rubén Caloto, Xosé R. Bustelo,
Tópico(s)T-cell and Retrovirus Studies
ResumoArticle7 October 2021Open Access Source DataTransparent process Cancer-associated mutations in VAV1 trigger variegated signaling outputs and T-cell lymphomagenesis Javier Robles-Valero Javier Robles-Valero orcid.org/0000-0001-5218-0187 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Lucía Fernández-Nevado Lucía Fernández-Nevado orcid.org/0000-0002-1757-6650 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author L Francisco Lorenzo-Martín L Francisco Lorenzo-Martín orcid.org/0000-0003-4717-9338 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Myriam Cuadrado Myriam Cuadrado orcid.org/0000-0001-9410-1205 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Isabel Fernández-Pisonero Isabel Fernández-Pisonero orcid.org/0000-0002-5130-2143 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Sonia Rodríguez-Fdez Sonia Rodríguez-Fdez orcid.org/0000-0001-5369-2969 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Elsa N Astorga-Simón Elsa N Astorga-Simón orcid.org/0000-0002-2317-1094 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Antonio Abad Antonio Abad orcid.org/0000-0001-8019-2775 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Rubén Caloto Rubén Caloto orcid.org/0000-0003-1325-896X Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Xosé R Bustelo Corresponding Author Xosé R Bustelo [email protected] orcid.org/0000-0001-9398-6072 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Javier Robles-Valero Javier Robles-Valero orcid.org/0000-0001-5218-0187 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Lucía Fernández-Nevado Lucía Fernández-Nevado orcid.org/0000-0002-1757-6650 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author L Francisco Lorenzo-Martín L Francisco Lorenzo-Martín orcid.org/0000-0003-4717-9338 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Myriam Cuadrado Myriam Cuadrado orcid.org/0000-0001-9410-1205 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Isabel Fernández-Pisonero Isabel Fernández-Pisonero orcid.org/0000-0002-5130-2143 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Sonia Rodríguez-Fdez Sonia Rodríguez-Fdez orcid.org/0000-0001-5369-2969 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Elsa N Astorga-Simón Elsa N Astorga-Simón orcid.org/0000-0002-2317-1094 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Antonio Abad Antonio Abad orcid.org/0000-0001-8019-2775 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Rubén Caloto Rubén Caloto orcid.org/0000-0003-1325-896X Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Xosé R Bustelo Corresponding Author Xosé R Bustelo [email protected] orcid.org/0000-0001-9398-6072 Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain Search for more papers by this author Author Information Javier Robles-Valero1,2,3, Lucía Fernández-Nevado1,2,3, L Francisco Lorenzo-Martín1,2,3, Myriam Cuadrado1,2,3, Isabel Fernández-Pisonero1,2,3, Sonia Rodríguez-Fdez1,2,3, Elsa N Astorga-Simón1,2, Antonio Abad1,3, Rubén Caloto1,2,3 and Xosé R Bustelo *,1,2,3 1Molecular Mechanisms of Cancer Program, Centro de Investigación del Cáncer, CSIC-University of Salamanca, Salamanca, Spain 2Instituto de Biología Molecular y Celular del Cáncer, CSIC-University of Salamanca, Salamanca, Spain 3Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), CSIC-University of Salamanca, Salamanca, Spain *Corresponding author. Tel: +34 663 194 634; E-mail: [email protected] The EMBO Journal (2021)40:e108125https://doi.org/10.15252/embj.2021108125 PDFDownload PDF of article text and main figures.PDF PLUSDownload PDF of article text, main figures, expanded view figures and appendix. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Mutations in VAV1, a gene that encodes a multifunctional protein important for lymphocytes, are found at different frequencies in peripheral T-cell lymphoma (PTCL), non-small cell lung cancer, and other tumors. However, their pathobiological significance remains unsettled. After cataloguing 51 cancer-associated VAV1 mutations, we show here that they can be classified in five subtypes according to functional impact on the three main VAV1 signaling branches, GEF-dependent activation of RAC1, GEF-independent adaptor-like, and tumor suppressor functions. These mutations target new and previously established regulatory layers of the protein, leading to quantitative and qualitative changes in VAV1 signaling output. We also demonstrate that the most frequent VAV1 mutant subtype drives PTCL formation in mice. This process requires the concurrent engagement of two downstream signaling branches that promote the chronic activation and transformation of follicular helper T cells. Collectively, these data reveal the genetic constraints associated with the lymphomagenic potential of VAV1 mutant subsets, similarities with other PTCL driver genes, and potential therapeutic vulnerabilities. Synopsis VAV1 encodes a multifunctional signaling protein involved in both RAC1 GTPase activation and adaptor-like functions. Mutations in this gene have recently been found in PTCL and other tumor types. Here, we have catalogued 51 VAV1 tumor-associated mutations according to their functional impact on the downstream signaling branches of the protein. Our work has revealed that: The VAV1 gain-of-function mutations belong to different subclasses according to impact on VAV1 downstream signaling. These mutations target both expected and hitherto unknown VAV1 regulatory layers. A VAV1 mutation representative of the most frequent functional subclass drives PTCL formation in mice. VAV1-driven lymphomagenesis requires cooperating signals from the catalytic-dependent and independent pathways of the mutant protein. The molecular features of VAV1-driven lymphomas resemble those found in PTCL patients. Introduction VAV1 is a multifunctional protein that plays signaling amplification and diversification roles downstream of the T-cell receptor (TCR) (Bustelo, 2014; Rodriguez-Fdez & Bustelo, 2019). One of the main functions of VAV1 is to catalyze the activation of the RHO GTPase RAC1 (Crespo et al, 1997; Bustelo, 2014; Rodriguez-Fdez & Bustelo, 2019) (Fig 1A). This enzyme reaction is mediated by a central cassette of the protein composed of the catalytic Dbl homology (DH) domain and the adjacent pleckstrin homology (PH) and C1-subtype zinc finger (ZF) regions (Fig EV1A) (Movilla & Bustelo, 1999; Zugaza et al, 2002; Chrencik et al, 2008; Rapley et al, 2008; Bustelo, 2014; Rodriguez-Fdez & Bustelo, 2019). The activation of RAC1 leads to the remodeling of the F-actin cytoskeleton and the stimulation of downstream elements such as the cJun N-terminal kinase (JNK) and the transcriptional factors AP1 and serum responsive factor (SRF) (Bustelo, 2014; Rodriguez-Fdez & Bustelo, 2019). VAV1 also activates other signal transduction pathways using adaptor, catalysis-independent mechanisms. One of them is the stimulation via the VAV1 calponin homology (CH) domain of a phospholipase Cγ1 (PLCγ1)-dependent pathway that leads to the stimulation of the nuclear factor of activated T cells (NFAT) (Fig 1A) (Wu et al, 1995; Kuhne et al, 2000). NFAT is involved in the regulation of proliferation and cytokine production by T cells (Muller & Rao, 2010). More recently, it has been involved in other T-cell-specific responses such as the differentiation of follicular helper T (TFH) cells (Martinez et al, 2016). A target of NFAT, the thymocyte selection-associated HMG-box protein (TOX) (Scott et al, 2019), is also involved in this latter differentiation process (Xu et al, 2019). Another adaptor-like function of VAV1, which is associated with tumor suppressor roles in T-cell acute lymphoblastic leukemia of the TLX+ subtype, is the negative regulation of the active intracellular fragment of NOTCH1 (ICN1) (Fig 1A) (Robles-Valero et al, 2017). This pathway is mediated by the most C-terminal VAV1 SH3 (CSH3), which promotes the ubiquitin-mediated degradation of ICN1 by forming complexes with the E3 ubiquitin ligase CBL-B (Casitas B-lineage lymphoma B) (Robles-Valero et al, 2017). The VAV1 CSH3 can bind to additional partners such as the heterogeneous nuclear ribonucleoprotein K (HNRNPK) and dynamin 2 (DNM2) (Bustelo et al, 1995; Gomez et al, 2005), suggesting that VAV1 might play additional adaptor-like functions both in normal and cancer cells. Figure 1. Functional impact of VAV1 mutations in the RAC1 and NFAT pathways A. Depiction of the three main signaling branches of VAV1 in T cells. Additional binding partners of the CSH3 domain that will be studied in this work are also shown. Signaling crosstalk between the NFAT route and parallel TCR-triggered pathways is also depicted. DAG, diacylglycerol; RAS-GRP1, Ras GDP releasing protein 1; cNFAT, cytosolic NFAT; nNFAT, nuclear NFAT. Rest of abbreviations have been introduced in the main text. B. Vav1-dependent biological readouts and cell types used to test the biological activity of Vav1 mutant proteins. The color of each assay represents the VAV1-regulated downstream pathway shown in panel (A). Please, note that the GTPase activation and protein–protein interaction experiments were done with smaller subsets of mutants than the JNK, SRF, and NFAT experiments. C, D. Heatmap representations summarizing the activity of VAV1 mutants (top) in the indicated assays tested (left). The mutations are clustered according to their specific distribution within the primary structure of the protein (C) and type of behavior in these experiments with the rest of mutants tested (D). Activity scores are depicted on a dark blue (lowest activity) to dark red (highest activity) scale relative to the activity levels found for Vav1WT under nonstimulated conditions (which was given an arbitrary value of 1) (n = 3 independent experiments, each performed in triplicate). The color code used for each mutant is associated with the biological activity exhibited in these assays following the color code indicated in (C) (bottom box). DGOF, double gain of function in RAC1 and NFAT pathways; RSGOF, RAC1 single gain of function; NSGOF, NFAT single gain of function; DLOF, double loss of function; NSLOF, NFAT single loss of function; SG+SLOF, RAC1 gain of function and NFAT loss of function. The laboratory-made VAV1 mutants used as positive control are indicated by asterisks. E. Heatmap representation summarizing the activity of VAV1 mutants (top) in COS (left panel) and Jurkat (right panel) cells on the indicated GTPases. Activity scores are depicted on a white (WT activity) to dark red (highest activity) scales relative to the activity levels found for Vav1WT (which was given an arbitrary value of 1). n = 3 independent experiments, each performed in duplicate. The color code used for each mutant is as in panels (C and D). Activated RHO-GTPase proteins (Rac1Q61L, RhoAQ63L, and Cdc42Q61L) were used as positive control in the appropriate assay. F. Top, heatmap summarizing the results obtained in our GST pull-down experiments with the indicated CSH3 mutant proteins. Binding partners tested are shown on the left. The mutations are represented in a sequential manner and following the color code used in panels (C and D). Activity scores are depicted on a dark blue (lowest interaction) to dark red (highest interaction) scale relative those obtained with the CSH3WT (which was given an arbitrary value of 1) (n = 3 independent experiments). Bottom, heatmap showing the biological activity of the indicated CSH3 mutants obtained in the experiments described in panels (C and D). This heatmap has been included to facilitate the comparison of the activities of these mutants in all the assays used in this figure. Source data are available online for this figure. Source Data for Figure 1 [embj2021108125-sup-0006-SDataFig1.xlsx] Download figure Download PowerPoint Click here to expand this figure. Figure EV1. Tumor-associated VAV1 mutations Localization of VAV1 missense mutations identified in PTCL (top) and NSCLC (bottom) in the primary structure of the protein. Each dot represents one patient. Abbreviations for domains have been described in main text. Mutations analyzed in this study are shown in gray color. The main pathways activated by the VAV1 domains are indicated. CH, calponin homology; Ac, acidic; DH, Dbl homology; PH, pleckstrin homology; ZF, zinc finger; NSH3, most N-terminal SH3 domain; CSH3, most C-terminal SH3. Examples of C-terminal truncations (top, proteins 1 to 6), translocations affecting the C-terminal end (middle, proteins 7 to 11, fused protein indicated as a violet box), and internal gene deletions (bottom, proteins 12 to 14) found in human patients. Mutations analyzed in this study are shown in gray font. Those not tested are in black font. Download figure Download PowerPoint One of the main regulatory features of VAV1 is that its ability to stimulate both the RAC1 and NFAT pathways is highly dependent on its tyrosine phosphorylation state (Bustelo, 2014). Thus, in nonstimulated cells, nonphosphorylated VAV1 is in an inactive state due to inhibitory interactions established by the N-terminal (CH and acidic region) domains and the CSH3 region with the central DH-PH-ZF cassette. These interactions are eliminated upon the phosphorylation of VAV1 on tyrosine residues located on the acidic (Ac), ZF, and CSH3 regions. This activation step is mediated in trans by the SH2 and most N-terminal SH3 (NSH3) region that facilitate the interaction of VAV1 with upstream protein tyrosine kinases and adaptor molecules, respectively (Bustelo, 2014). VAV1 was identified in 1989 due to its oncogenic activity in focus formation assays (Katzav et al, 1989). Despite this, its role in cancer has been circumscribed so far to the upregulation of the wild-type protein (Bustelo, 2014). This has changed recently, since the characterization of cancer genomes has revealed that VAV1 is frequently mutated in a number of PTCL subtypes such as adult T-cell leukemia/lymphoma (ATLL, 17% of total cases), PTCL-not otherwise specified (PTCL-NOS, 7% of total cases), and angioimmunoblastic T-cell lymphoma (AITL, 6% of total cases) (Yoo et al, 2014; Crescenzo et al, 2015; Kataoka et al, 2015; Boddicker et al, 2016; Vallois et al, 2016; Abate et al, 2017; Park et al, 2017). Mutations have also been detected at much lower frequencies in anaplastic large cell lymphoma (ALCL), cutaneous T-cell lymphoma (CTCL), and non-small-cell lung cancer (NSCLC) (Crescenzo et al, 2015; Boddicker et al, 2016; Campbell et al, 2016; Abate et al, 2017; Park et al, 2017) (Fig EV1A and B). The actual relevance of these mutations from a functional and pathobiological perspective remains, however, ill-defined. In this context, recent studies have shown that some tumor-associated VAV1 mutations lead indeed to gain-of-function (GOF) events (Boddicker et al, 2016; Abate et al, 2017; Fukumoto et al, 2020). However, these analyses have been limited to a very small (8%) and overlapping subset of mutations that target obvious regulatory layers of the protein. Moreover, those studies have not tested all the spectrum of downstream signals elicited by this protein (Boddicker et al, 2016; Abate et al, 2017; Fukumoto et al, 2020). As a result, we do not know yet whether most VAV1 mutations found in tumors act as bona fide oncogenic drivers in vivo and, if so, whether they do it autonomously or in combination with ancillary inputs from other genetic lesions and/or cancer cell-extrinsic events. Likewise, we do not know the spectrum of downstream signaling pathways that have to be engaged to promote full cell transformation. To address these relevant knowledge gaps, we have measured qualitatively and quantitatively the functional impact of 51 VAV1 mutations found in tumors on all known VAV1-dependent signaling outputs. This strategy allowed us to generate a comprehensive signaling and functional catalogue of the tumor-associated VAV1 mutations. Using adoptive cell transfer experiments, we have also demonstrated that the most frequent functional subclass of VAV1 mutations identified in our study can drive AITL formation. Finally, we have identified the main signaling and pathobiological programs involved in the generation of Vav1-driven tumors using a combination of cellular, signaling, and genome-wide gene expression approaches. These findings suggest that VAV1 mutations probably play clinical-relevant roles in AITL and other tumor types. They also pinpoint several VAV1 signaling-based pharmacological strategies to treat them. Results Variegated functional impacts of VAV1 mutations found in tumors To start building a functional catalogue of the VAV1 mutations present in tumors, we decided to comprehensively analyze the impact of 51 mutations recently found in PTCL and NSCLC (Fig EV1A and B) using several experimental readouts for the main downstream signaling pathways engaged by this protein (Fig 1A and B). The mutations tested encompassed an internal deletion, four fusions, four truncations, and 42 missense changes. In the case of point mutations, we included in the analyses allelic variants found in some codons. First, we investigated the impact of the 51 mutations on the two main catalysis-dependent (RAC1–JNK and RAC1–SRF) and CH-dependent (PLCγ1–NFAT) pathways regulated by VAV1 (Fig 1B). To this end, we carried out in the former case luciferase-based reporter assays to measure the effect of the interrogated mutant proteins on the activity of both JNK and SRF in Jurkat (nonstimulated and TCR-stimulated) and exponentially growing COS1 cells, respectively (Fig 1B). In the case of the NFAT pathway, we carried out luciferase-based reporter experiments in nonstimulated and TCR-stimulated Jurkat cells to measure the impact of the mutants in the transcriptional activity of an Il2 promoter containing three NFAT-binding sites (Fig 1B). It is worth noting that, unlike the case of RAC1-dependent pathways, the optimal stimulation of the NFAT pathway by VAV1 requires parallel signaling inputs from the antigen receptor in this assay. As a result, the activation of this transcriptional factor is enhanced upon the engagement of the TCR even in T cells that express fully deregulated, constitutively active VAV1 versions (Barreira et al, 2014). As positive control, we included in these analyses the lab-made Vav1Y174E and Vav1Y174F mutant proteins that are known to promote high levels of stimulation of both the RAC1 and NFAT pathways (Lopez-Lago et al, 2000; Barreira et al, 2014). The results obtained for all the interrogated Vav1 mutants in these assays, compared with the reference basal (Vav1WT) and positive (Vav1Y174F, Vav1Y174E) controls, are collectively depicted using a heatmap representation in Fig 1C and D. The wet-lab data used to generate these heatmaps are shown both in the Appendix Figs S1–S8. Using this approach, we found that 25% of the interrogated mutations elicit a bivalent GOF effect on the RAC1 and NFAT pathways (Fig 1C and D; residues shown in red). These mutants can be further subdivided according to their specific impact on the signaling output of the protein as weak (e.g., E556D), intermediate (e.g., Y174C, G819S), and strong (e.g., Δ820–845) (Fig 1D). Only the latter ones, which are associated with the generation of C-terminally truncated and fusion proteins, exhibit fully constitutive, phosphorylation-independent biological activity (Fig 1D). More unexpectedly, we observed that 12% of the VAV1 mutations display signaling branch-specific effects that cause the specific stimulation of either the RAC1 or the NFAT pathway (Fig 1C and D; residues labeled in red and blue colors at the same time). Finally, 63% of the interrogated mutations show either WT-like (47%, Fig 1C and D; residues labeled in green) or reduced activity in these two assays (16%, Fig 1C and D; residues labeled in blue). It is worth noting, however, that some of these mutants will induce the elimination of the tumor suppressor pathway regulated by VAV1 and, therefore, must have an impact in Notch1 signaling (see below in this section). As a complementary avenue to the data obtained using the indirect JNK and SRF assays, we used the G-LISA method to test the direct effect of 3 VAV1 mutants belonging to the bivalent (Y174C, G819S) and signaling branch-specific (R678Q) subsets on the activation of the three main RHO family GTPases in both COS1 and Jurkat cells. As positive controls, we utilized constitutively active versions of VAV1 (Δ1-189 and Δ835-845), RAC1 (Q61L), RHOA (Q63L), and CDC42 (Q61L). When compared to VAV1WT, we found that all the chosen VAV1 mutants could activate the incorporation of GTP onto RAC1 irrespectively of the functional subclass involved (Fig 1E and Appendix Fig S9). By contrast, they exhibited much lower activities on RHOA and CDC42 (Fig 1E and Appendix Fig S9). This RAC1 specificity is consistent with previous biochemical and cell-based experiments (Crespo et al, 1997; Aghazadeh et al, 2000; Couceiro et al, 2005; Rapley et al, 2008). We next investigated the effect of specific mutations on the recently described tumor suppressor pathway regulated by VAV1 (Fig 1A). According to our previous data (Robles-Valero et al, 2017), this function must be lost in the case of all the truncation and translocation VAV1 mutants that have lost the CSH3 domain. In agreement with this, we found that the Vav1Δ677–845 protein cannot coimmunoprecipitate CBL-B when expressed in Jurkat cells (Fig EV2A). The role of this mutation must be specifically associated with the elimination of this suppressor pathway, given that Vav1Δ677–845 shows reduced activity when tested in the JNK, SRF, and NFAT assays (see above, Fig 1C). By contrast, VAV1WT and versions of VAV1 with mutations outside the CSH3 that exhibit WT-like activities in the previous assays (Fig 1C) do associate with this E3 ubiquitin ligase (Fig EV2A). This suggests that these latter mutations are probably bystanders. Since missense mutations targeting residues located in the CSH3 can also lead to the loss of the suppressor function (Robles-Valero et al, 2017), we next carried out GST pull-down experiments to evaluate the interaction of the 13 VAV1 CSH3 point mutants with CBL-B, HNRNPK, and DNM2. As negative control, we used the nonchimeric GST protein and, in some experiments, a GST fusion protein containing a mutant version of the VAV1 CSH3 (P833L) that cannot interact with any known protein partner (Barreira et al, 2014; Robles-Valero et al, 2017). As positive control, we used a GST-VAV1 CSH3WT fusion protein as bait. A heatmap summarizing the data obtained in all these experiments is shown in Fig 1F. The raw data can be found in Fig EV2B–D. These analyses revealed that 65% of the Vav1 CSH3 mutants analyzed have impaired physical interactions with CBL-B and the other two protein partners (Fig 1F, see scheme in Fig EV2E). They also identified a smaller subset (15%) of Vav1 CSH3 mutants with a selective impairment of the interaction with either HNRNPK (E805K, R822Q) or DNM2 (D797N) (Fig 1F, see scheme in Fig EV2E). Click here to expand this figure. Figure EV2. CSH3 mutations alter the interaction between VAV1 and binding partners A. Co-immunoprecipitation of indicated Vav1 proteins with CBL-B in Jurkat cells ectopically expressing the indicated combinations of proteins (top). Amount of immunoprecipitated CBL-B was assessed by reblotting the same filter with antibodies to CBL-B (second panel from top). Expression of ectopic VAV1 proteins (third panel from top) and endogenous tubulin α (loading control, bottom panel) was determined by immunoblotting using aliquots of the total cellular lysates used
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