Vav Activation and Function as a Rac Guanine Nucleotide Exchange Factor in Macrophage Colony-Stimulating Factor-Induced Macrophage Chemotaxis

Signal transduction mediated by phosphatidylinositol 3-kinase (PI 3-kinase) is regulated by hydrolysis of its products, a function performed by the 145-kDa SH2 domain-containing inositol phosphatase (SHIP). Here, we show that bone marrow macrophages of SHIP(−/−) animals have elevated levels of phosphatidylinositol 3,4,5-trisphosphate [PI (3,4,5)P(3)] and displayed higher and more prolonged chemotactic responses to macrophage colony-stimulating factor (M-CSF) and elevated levels of F-actin relative to wild-type macrophages. We also found that the small GTPase Rac was constitutively active and its upstream activator Vav was constitutively phosphorylated in SHIP(−/−) macrophages. Furthermore, we show that Vav in wild-type macrophages is recruited to the membrane in a PI 3-kinase-dependent manner through the Vav pleckstrin homology domain upon M-CSF stimulation. Dominant inhibitory mutants of both Rac and Vav blocked chemotaxis. We conclude that Vav acts as a PI 3-kinase-dependent activator for Rac activation in macrophages stimulated with M-CSF and that SHIP regulates macrophage M-CSF-triggered chemotaxis by hydrolysis of PI (3,4,5)P(3)

Real-Time Motion Analysis Reveals Cell Directionality as an Indicator of Breast Cancer Progression

<div><p>Cancer cells alter their migratory properties during tumor progression to invade surrounding tissues and metastasize to distant sites. However, it remains unclear how migratory behaviors differ between tumor cells of different malignancy and whether these migratory behaviors can be utilized to assess the malignant potential of tumor cells. Here, we analyzed the migratory behaviors of cell lines representing different stages of breast cancer progression using conventional migration assays or time-lapse imaging and particle image velocimetry (PIV) to capture migration dynamics. We find that the number of migrating cells in transwell assays, and the distance and speed of migration in unconstrained 2D assays, show no correlation with malignant potential. However, the directionality of cell motion during 2D migration nicely distinguishes benign and tumorigenic cell lines, with tumorigenic cell lines harboring less directed, more random motion. Furthermore, the migratory behaviors of epithelial sheets observed under basal conditions and in response to stimulation with epidermal growth factor (EGF) or lysophosphatitic acid (LPA) are distinct for each cell line with regard to cell speed, directionality, and spatiotemporal motion patterns. Surprisingly, treatment with LPA promotes a more cohesive, directional sheet movement in lung colony forming MCF10CA1a cells compared to basal conditions or EGF stimulation, implying that the LPA signaling pathway may alter the invasive potential of MCF10CA1a cells. Together, our findings identify cell directionality as a promising indicator for assessing the tumorigenic potential of breast cancer cell lines and show that LPA induces more cohesive motility in a subset of metastatic breast cancer cells.</p> </div

The migratory phenotype of MDA-MB 231T is similar to that of M4 cells.

<p>(<b>A</b>) Phase contrast images of MDA-MB-231T cells moving into open space after 12 h under control (Black), 5 ng/mL EGF (red), and 1 µM LPA (blue) treatments. Bar = 100 µm. (<b>B</b>) Right: The effects of EGF and LPA treatment on average speed (top) and directionality, CV (bottom) determined over all times and space, were compiled from 5–6 independent experiments and reported as mean ± SD. Left: Aggregate directionality profiles for control, EGF and LPA conditions. Statistical significance: *p<0.05 (Tukey-Kramer test, n = 3). (<b>C</b>) Representative spatiotemporal heat plots show speed responses in control, EGF, and LPA treated cells. See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058859#pone-0058859-g004" target="_blank">Fig. 4</a> for details.</p

Cell lines of the MCF10A series show distinct responses to EGF and LPA.

<p>(<b>A–D</b>) M1–M4 cells were stimulated with 5 ng/mL EGF (red) or 1 µM LPA (blue) and perturbations of average speed and of directionality (angle distributions and CV) compared to controls (black) were assessed (mean ± SD). Rose plots depict controls (unfilled, black bars) and 5 ng/mL EGF (filled, red bars) or 1 µM LPA (filled, blue bars). Statistical significance: * p<0.05, ** p<0.01, *** p<0.001 (Tukey-Kramer test, n = 3 for all conditions except M2 with EGF where n = 2). All comparisons were made with M1 cells unless indicated by pairing-brackets.</p

Cell lines of the MCF10A series show distinct migration properties.

<p>(<b>A</b>) Migration potential of M1–M2 (benign, black circles) and M3–M4 (tumorigenic, red triangles) cell lines after 4 h was assessed with the transwell assay using collagen IV coated membranes and no biased stimulation (see also <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0058859#pone.0058859.s001" target="_blank">Fig. S1A</a>). (<b>B</b>) Phase images of the M1–M4 cell lines after 0 and 12 h of unconstrained migration. The dash vertical line indicates the initial location of the sheet edge. Scale bar  = 100 µm. (<b>C</b>) Quantification of the net displacement (during the 3–12 h time frame) is presented as in panel A. (<b>D</b>) M1–M4 cells were first pretreated with 25 µg/mL Mitomycin C for 20 min and then allowed to migrate into open space under conditions identical to panel B (black bars). The net displacement (mean ± SD) is shown compared to control (w/o drug) conditions (white bars), n = 2. For panels A and C results are presented as mean ±95% CI of 6–7 independent experiments. Statistical significance: * p<0.05, ** p<0.01, *** p<0.001, ****p<0.0001 (Tukey-Kramer test, n = 6–7). All comparisons were made with M1 cells unless indicated by pairing-brackets.</p

Cell lines of the MCF10A series show distinct migration speed and directionality.

<p>(<b>A</b>) PIV analysis enables the mapping of velocity fields associated with the underlying epithelial sheet motions captured by phase time-lapse imaging (scale bar  = 100 µm). Spatial profiles of directionality and speed are depicted with white vectors and a heat map, respectively (right panel). (<b>B</b>) Left: Aggregate speed distributions, determined over all times and space, were compiled from 5–6 independent experiments for each cell line. Right: Quantification of the mean of the average speed (mean ±95% CI) for each cell line; M1–M2 (benign, black circles) and M3–M4 (tumorigenic, red triangles). (<b>C</b>) Left: Rose plots depicting aggregate directionality distributions were compiled over all times and space for each cell line (n = 5–6). Right: Variability of the direction of motion was quantified by the coefficient of variation (CV) and reported as mean ±95% CI. Statistical significance: * p<0.05, ** p<0.01, *** p<0.001 (Tukey-Kramer test, n = 5–6). All comparisons were made with M1 cells unless indicated by pairing-brackets.</p

The Transcriptomic Portrait of Locally Advanced Breast Cancer and Its Prognostic Value in a Multi-Country Cohort of Latin American Patients

Purposes: Most molecular-based published studies on breast cancer do not adequately represent the unique and diverse genetic admixture of the Latin American population. Searching for similarities and differences in molecular pathways associated with these tumors and evaluating its impact on prognosis may help to select better therapeutic approaches. Patients and Methods: We collected clinical, pathological, and transcriptomic data of a multi-country Latin American cohort of 1,071 stage II-III breast cancer patients of the Molecular Profile of Breast Cancer Study (MPBCS) cohort. The 5-year prognostic ability of intrinsic (transcriptomic-based) PAM50 and immunohistochemical classifications, both at the cancer-specific (OSC) and disease-free survival (DFS) stages, was compared. Pathway analyses (GSEA, GSVA and MetaCore) were performed to explore differences among intrinsic subtypes. Results: PAM50 classification of the MPBCS cohort defined 42·6% of tumors as LumA, 21·3% as LumB, 13·3% as HER2E and 16·6% as Basal. Both OSC and DFS for LumA tumors were significantly better than for other subtypes, while Basal tumors had the worst prognosis. While the prognostic power of traditional subtypes calculated with hormone receptors (HR), HER2 and Ki67 determinations showed an acceptable performance, PAM50-derived risk of recurrence best discriminated low, intermediate and high-risk groups. Transcriptomic pathway analysis showed high proliferation (i.e. cell cycle control and DNA damage repair) associated with LumB, HER2E and Basal tumors, and a strong dependency on the estrogen pathway for LumA. Terms related to both innate and adaptive immune responses were seen predominantly upregulated in Basal tumors, and, to a lesser extent, in HER2E, with respect to LumA and B tumors. Conclusions: This is the first study that assesses molecular features at the transcriptomic level in a multicountry Latin American breast cancer patient cohort. Hormone-related and proliferation pathways that predominate in PAM50 and other breast cancer molecular classifications are also the main tumor-driving mechanisms in this cohort and have prognostic power. The immune-related features seen in the most aggressive subtypes may pave the way for therapeutic approaches not yet disseminated in Latin America. Clinical Trial Registration: ClinicalTrials.gov (Identifier: NCT02326857). Copyright © 2022 Llera, Abdelhay, Artagaveytia, Daneri-Navarro, Müller, Velazquez, Alcoba, Alonso, Alves da Quinta, Binato, Bravo, Camejo, Carraro, Castro, Castro-Cervantes, Cataldi, Cayota, Cerda, Colombo, Crocamo, Del Toro-Arreola, Delgadillo-Cisterna, Delgado, Dreyer-Breitenbach, Fejerman, Fernández, Fernández, Fernández, Franco-Topete, Gabay, Gaete, Garibay-Escobar, Gómez, Greif, Gross, Guerrero, Henderson, Lopez-Muñoz, Lopez-Vazquez, Maldonado, Morán-Mendoza, Nagai, Oceguera-Villanueva, Ortiz-Martínez, Quintero, Quintero-Ramos, Reis, Retamales, Rivera-Claisse, Rocha, Rodríguez, Rosales, Salas-González, Sanchotena, Segovia, Sendoya, Silva-García, Trinchero, Valenzuela, Vedham, Zagame, United States-Latin American Cancer Research Network (US-LACRN) and Podhajcer.Fil: Llera, Andrea Sabina. Fundación Instituto Leloir-CONICET. Molecular and Cellular Therapy Laboratory; ArgentinaFil: Abdelhay, Eliana Saul Furquim Werneck. Instituto Nacional de Câncer. Bone Marrow Transplantation Unit; BrasilFil: Artagaveytia, Nora. Universidad de la República. Hospital de Clínicas Manuel Quintela; UruguayFil: Daneri-Navarro, Adrián. Universidad de Guadalajara; MéxicoFil: Müller, Bettina. Instituto Nacional del Cáncer; ChileFil: Velazquez, Carlos. Universidad de Sonora; MéxicoFil: Alcoba, Elsa B. Hospital Municipal de Oncología María Curie; ArgentinaFil: Alonso, Isabel. Centro Hospitalario Pereira Rossell; UruguayFil: Alves da Quinta, Daniela B. Fundación Instituto Leloir-CONICET. Molecular and Cellular Therapy Laboratory; ArgentinaFil: Alves da Quinta, Daniela B. Universidad Argentina de la Empresa (UADE). Instituto de Tecnología (INTEC); ArgentinaFil: Binato, Renata. Instituto Nacional de Câncer. Bone Marrow Transplantation Unit; BrasilFil: Bravo, Alicia Inés. Hospital Regional de Agudos Eva Perón; ArgentinaFil: Camejo, Natalia. Universidad de la República. Hospital de Clínicas Manuel Quintela; UruguayFil: Carraro, Dirce Maria. AC Camargo Cancer Center. Centro Internacional de Pesquisa (CIPE). Laboratory of Genomics and Molecular Biology; BrasilFil: Castro, Mónica. Instituto de Oncología Angel Roffo; ArgentinaFil: Castro-Cervantes, Juan M. Hospital de Especialidades CMNO-IMSS; MéxicoFil: Cataldi, Sandra. Instituto Nacional del Cáncer; UruguayFil: Cayota, Alfonso. Institut Pasteur de Montevideo; UruguayFil: Cerda, Mauricio. Universidad de Chile. Instituto de Neurociencias Biomédicas. Facultad de Medicina. Centro de Informática Médica y Telemedicina. Instituto de Ciencias Biomédicas (ICBM). Integrative Biology Program; ChileFil: Colombo, Alicia. Universidad de Chile. Facultad de Medicina y Hospital Clínico. Department of Pathology; ChileFil: Crocamo, Susanne. Instituto Nacional de Câncer. Oncology Department; BrasilFil: Del Toro-Arreola, Alicia. Universidad de Guadalajara; MéxicoFil: Delgadillo-Cisterna, Raúl. Hospital de Especialidades CMNO-IMSS; MéxicoFil: Delgado, Lucía. Universidad de la República. Hospital de Clínicas Manuel Quintela; UruguayFil: Dreyer-Breitenbach, Marisa. Universidade do Estado do Rio de Janeiro. Instituto de Biologia Roberto Alcantara Gomes; BrasilFil: Fejerman, Laura. University of California Davis. Department of Public Health Sciences and Comprehensive Cancer Center; Estados UnidosFil: Fernández, Elmer A. Universidad Católica de Córdoba. CONICET. Centro de Investigación y Desarrollo en Inmunología y Enfermedades Infecciosas [Centro de Investigación y Desarrollo en Inmunología y Enfermedades Infecciosas (CIDIE); ArgentinaFil: Fernández, Elmer A. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; ArgentinaFil: Fernández, Wanda. Hospital San Borja Arriarán; ChileFil: Franco-Topete, Ramón A. Universidad de Guadalajara. Hospital Civil de Guadalajara. Organismo Público Descentralizado (OPD); MéxicoFil: Gabay, Carolina. Instituto de Oncología Angel Roffo; ArgentinaFil: Gaete, Fancy. Hospital Luis Tisne; ChileFil: Garibay-Escobar, Adriana. Universidad de Sonora; MéxicoFil: Gómez, Jorge. Texas A&M University; Estados UnidosFil: Greif, Gonzalo. Institut Pasteur de Montevideo; UruguayFil: Gross, Thomas G. Center for Global Health, National Cancer Institute; Estados UnidosFil: Guerrero, Marisol. Hospital San José; ChileFil: Henderson, Marianne K. Center for Global Health, National Cancer Institute; Estados UnidosFil: Lopez-Muñoz, Miguel E. Universidad de Sonora; MéxicoFil: Lopez-Vazquez, Alejandra. Universidad de Sonora; MéxicoFil: Maldonado, Silvina. Hospital Regional de Agudos Eva Perón; ArgentinaFil: Morán-Mendoza, Andrés J. Hospital de Gineco-Obstetricia CMNO-IMSS; MéxicoFil: Nagai, Maria Aparecida. Sao Paulo University Medical School. Cancer Institute of São Paulo (ICESP). Center for Translational Research in Oncology; BrasilFil: Oceguera-Villanueva, Antonio. Instituto Jalisciense de Cancerologia; MéxicoFil: Ortiz-Martínez, Miguel A. Hospital General Regional No. 1. IMSS; MéxicoFil: Quintero, Jael. Universidad de Sonora; MéxicoFil: Quintero-Ramos, Antonio. Universidad de Guadalajara; MéxicoFil: Reis, Rui M. Hospital de Câncer de Barretos. Molecular Oncology Research Center; BrasilFil: Retamales, Javier. Grupo Oncológico Cooperativo Chileno de Investigación; ChileFil: Rivera-Claisse, Ernesto. Centro Estatal de Oncologia; MéxicoFil: Rocha, Darío. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; ArgentinaFil: Rodríguez, Robinson. Hospital Central de las Fuerzas Armadas; UruguayFil: Rosales, Cristina. Hospital Municipal de Oncología María Curie; ArgentinaFil: Salas-González, Efrain. Hospital de Gineco-Obstetricia CMNO-IMSS; MéxicoFil: Sanchotena, Verónica. Hospital Municipal de Oncología María Curie; ArgentinaFil: Segovia, Laura. Hospital Barros Luco Trudeau; ChileFil: Sendoya, Juan Martín. Fundación Instituto Leloir-CONICET. Molecular and Cellular Therapy Laboratory; ArgentinaFil: Silva-García, Aida A. Universidad de Guadalajara. Hospital Civil de Guadalajara. Organismo Público Descentralizado (OPD); MéxicoFil: Trinchero, Alejandra. Hospital Regional de Agudos Eva Perón; ArgentinaFil: Valenzuela, Olivia. Universidad de Sonora; MéxicoFil: Vedham, Vidya. National Cancer Institute. Center for Global Health; Estados Unido

The Transcriptomic Portrait of Locally Advanced Breast Cancer and Its Prognostic Value in a Multi-Country Cohort of Latin American Patients.

PurposesMost molecular-based published studies on breast cancer do not adequately represent the unique and diverse genetic admixture of the Latin American population. Searching for similarities and differences in molecular pathways associated with these tumors and evaluating its impact on prognosis may help to select better therapeutic approaches.Patients and methodsWe collected clinical, pathological, and transcriptomic data of a multi-country Latin American cohort of 1,071 stage II-III breast cancer patients of the Molecular Profile of Breast Cancer Study (MPBCS) cohort. The 5-year prognostic ability of intrinsic (transcriptomic-based) PAM50 and immunohistochemical classifications, both at the cancer-specific (OSC) and disease-free survival (DFS) stages, was compared. Pathway analyses (GSEA, GSVA and MetaCore) were performed to explore differences among intrinsic subtypes.ResultsPAM50 classification of the MPBCS cohort defined 42·6% of tumors as LumA, 21·3% as LumB, 13·3% as HER2E and 16·6% as Basal. Both OSC and DFS for LumA tumors were significantly better than for other subtypes, while Basal tumors had the worst prognosis. While the prognostic power of traditional subtypes calculated with hormone receptors (HR), HER2 and Ki67 determinations showed an acceptable performance, PAM50-derived risk of recurrence best discriminated low, intermediate and high-risk groups. Transcriptomic pathway analysis showed high proliferation (i.e. cell cycle control and DNA damage repair) associated with LumB, HER2E and Basal tumors, and a strong dependency on the estrogen pathway for LumA. Terms related to both innate and adaptive immune responses were seen predominantly upregulated in Basal tumors, and, to a lesser extent, in HER2E, with respect to LumA and B tumors.ConclusionsThis is the first study that assesses molecular features at the transcriptomic level in a multicountry Latin American breast cancer patient cohort. Hormone-related and proliferation pathways that predominate in PAM50 and other breast cancer molecular classifications are also the main tumor-driving mechanisms in this cohort and have prognostic power. The immune-related features seen in the most aggressive subtypes may pave the way for therapeutic approaches not yet disseminated in Latin America.Clinical trial registrationClinicalTrials.gov (Identifier: NCT02326857)