RESUMEN
Although systemic immunity is critical to the process of tumor rejection, cancer research has largely focused on immune cells in the tumor microenvironment. To understand molecular changes in the patient systemic response (SR) to the presence of BC, we profiled RNA in blood and matched tumor from 173 patients. We designed a system (MIxT, Matched Interactions Across Tissues) to systematically explore and link molecular processes expressed in each tissue. MIxT confirmed that processes active in the patient SR are especially relevant to BC immunogenicity. The nature of interactions across tissues (i.e. which biological processes are associated and their patterns of expression) varies highly with tumor subtype. For example, aspects of the immune SR are underexpressed proportionally to the level of expression of defined molecular processes specific to basal tumors. The catalog of subtype-specific interactions across tissues from BC patients provides promising new ways to tackle or monitor the disease by exploiting the patient SR.
Asunto(s)
Células Sanguíneas/fisiología , Neoplasias de la Mama/fisiopatología , Microambiente Celular/fisiología , Microambiente Tumoral/fisiología , Biomarcadores de Tumor/análisis , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Estudios de Casos y Controles , Femenino , Perfilación de la Expresión Génica , Genómica , Humanos , Persona de Mediana Edad , Transducción de Señal , Biología de SistemasRESUMEN
Lung cancer is the leading cause of cancer deaths. Novel predictive biomarkers are needed to improve treatment selection and more accurate prognostication. PAX6 is a transcription factor with a proposed tumour suppressor function. Immunohistochemical staining was performed on tissue microarrays from 335 non-small cell lung cancer (NSCLC) patients for PAX6. Multivariate analyses of clinico-pathological variables and disease-specific survival (DSS) was carried out, and phenotypic changes of two NSCLC cell lines with knockdown of PAX6 were characterized. While PAX6 expression was only associated with a trend of better disease-specific survival (DSS) (p = 0.10), the pN+ subgroup (N = 103) showed significant correlation between high PAX6 expression and longer DSS (p = 0.022). Median survival for pN + patients with high PAX6 expression was 127.4 months, versus 22.9 months for patients with low PAX6 expression. In NCI-H661 cells, knockdown of PAX6 strongly activated serum-stimulated migration. In NCI-H460 cells, PAX6 knockdown activated anchorage-independent growth. We did not observe any significant effect of PAX6 on proliferation in either of cell lines. Our findings strongly support the proposition of PAX6 as a valid and positive prognostic marker in NSCLC in node-positive patients. There is a need for further studies, which should provide mechanistical explanation for the role of PAX6 in NSCLC.
Asunto(s)
Biomarcadores de Tumor/genética , Carcinoma de Pulmón de Células no Pequeñas/genética , Proliferación Celular/genética , Factor de Transcripción PAX6/genética , Adulto , Anciano , Anciano de 80 o más Años , Carcinoma de Pulmón de Células no Pequeñas/patología , Línea Celular Tumoral , Supervivencia sin Enfermedad , Femenino , Regulación Neoplásica de la Expresión Génica/genética , Técnicas de Silenciamiento del Gen , Humanos , Ganglios Linfáticos/patología , Masculino , Persona de Mediana Edad , Estadificación de Neoplasias , Pronóstico , Proteínas Supresoras de Tumor/genéticaRESUMEN
Kvik is an open-source framework that we developed for explorative analysis of functional genomics data from large epidemiological studies. Creating such studies requires a significant amount of time and resources. It is therefore usual to reuse the data from one study for several research projects. Often each project requires implementing new analysis code, integration with specific knowledge bases, and specific visualizations. Although existing data exploration tools are available for single study data exploration, no tool provides all the required functionality for multistudy data exploration. We have therefore used the Kvik framework to develop Kvik Pathways, an application for exploring gene expression data in the context of biological pathways. We have used Kvik Pathways to explore data from both a cross-sectional study design and a case-control study within the Norwegian Women and Cancer (NOWAC) cohort. Kvik Pathways follows the three-tier architecture in web applications using a powerful back-end for statistical analyses and retrieval of metadata.In this note, we describe how we used the Kvik framework to develop the Kvik Pathways application. Kvik Pathways was used by our team of epidemiologists toexplore gene expression data from healthy women with high and low plasma ratios of essential fatty acids.