RESUMEN
We assessed the association of metformin use with survival in colorectal cancer in a population consists mostly of African-American and Afro-Caribbean patients. We identified 585 colorectal cancer patients, 167 (28.6%) and 418 (71.5%) were as diabetic (DM) and nondiabetic, respectively. The diagnosis of diabetes did not impact cancer survival or extent of disease. Overall, DMs with metformin use (D+M+) have better overall survival than both DMs without metformin use (D+Mâ¼) and nondiabetics (Dâ¼Mâ¼), with a mean survival of 109.9 months compared with 95.7 and 106.1 months, respectively (log-rank p < 0.05). The use of metformin shows significant reduction of risk of mortality compared with nonusers (hazard ratio: 0.34; 95% CI: 0.15-0.81; p = 0.01). Use of insulin and status of diabetes did not have a significant impact on overall cancer survival.
RESUMEN
Osteosarcoma (OS) is a highly aggressive pediatric bone cancer in which most tumor cells remain immature and fail to differentiate into bone-forming osteoblasts. However, OS cells readily respond to adipogenic stimuli suggesting they retain mesenchymal stem cell-like properties. Here we demonstrate that nuclear receptor PPARγ agonists such as the anti-diabetic, thiazolidinedione (TZD) drugs induce growth arrest and cause adipogenic differentiation in human, mouse and canine OS cells as well as in tumors in mice. Gene expression analysis reveals that TZDs induce lipid metabolism pathways while suppressing targets of the Hippo-YAP pathway, Wnt signaling and cancer-related proliferation pathways. Significantly, TZD action appears to be restricted to the high Sox2 expressing cancer stem cell population and is dependent on PPARγ expression. TZDs also affect growth and cell fate by causing the cytoplasmic sequestration of the transcription factors SOX2 and YAP that are required for tumorigenicity. Finally, we identify a TZD-regulated gene signature based on Wnt/Hippo target genes and PPARγ that predicts patient outcomes. Together, this work highlights a novel connection between PPARγ agonist in inducing adipogenesis and mimicking the tumor suppressive hippo pathway. It also illustrates the potential of drug repurposing for TZD-based differentiation therapy for osteosarcoma.
Asunto(s)
Proteínas Adaptadoras Transductoras de Señales/metabolismo , Osteosarcoma/metabolismo , PPAR gamma/agonistas , PPAR gamma/metabolismo , Fosfoproteínas/metabolismo , Adipocitos/citología , Adipogénesis , Animales , Ciclo Celular , Proteínas de Ciclo Celular , Diferenciación Celular , Línea Celular Tumoral , Movimiento Celular , Proliferación Celular , Perros , Vía de Señalización Hippo , Humanos , Metabolismo de los Lípidos , Ratones , Ratones Endogámicos NOD , Ratones SCID , Trasplante de Neoplasias , Células Madre Neoplásicas/metabolismo , Osteosarcoma/genética , Proteínas Serina-Treonina Quinasas/metabolismo , Rosiglitazona , Transducción de Señal , Tiazolidinedionas/química , Factores de Transcripción , Proteínas Wnt/metabolismo , Proteínas Señalizadoras YAPRESUMEN
The repressive Hippo pathway has a profound tumour suppressive role in cancer by restraining the growth-promoting function of the transcriptional coactivator, YAP. We previously showed that the stem cell transcription factor Sox2 maintains cancer stem cells (CSCs) in osteosarcomas. We now report that in these tumours, Sox2 antagonizes the Hippo pathway by direct repression of two Hippo activators, Nf2 (Merlin) and WWC1 (Kibra), leading to exaggerated YAP function. Repression of Nf2, WWC1 and high YAP expression marks the CSC fraction of the tumor population, while the more differentiated fraction has high Nf2, high WWC1 and reduced YAP expression. YAP depletion sharply reduces CSCs and tumorigenicity of osteosarcomas. Thus, Sox2 interferes with the tumour-suppressive Hippo pathway to maintain CSCs in osteosarcomas. This Sox2-Hippo axis is conserved in other Sox2-dependent cancers such as glioblastomas. Disruption of YAP transcriptional activity could be a therapeutic strategy for Sox2-dependent tumours.
Asunto(s)
Regulación Neoplásica de la Expresión Génica , Glioblastoma/genética , Células Madre Neoplásicas/metabolismo , Osteosarcoma/genética , Proteínas Serina-Treonina Quinasas/genética , ARN Mensajero/metabolismo , Factores de Transcripción SOXB1/genética , Proteínas Adaptadoras Transductoras de Señales/genética , Proteínas Adaptadoras Transductoras de Señales/metabolismo , Línea Celular Tumoral , Glioblastoma/metabolismo , Vía de Señalización Hippo , Humanos , Péptidos y Proteínas de Señalización Intracelular/genética , Péptidos y Proteínas de Señalización Intracelular/metabolismo , Neurofibromina 2/genética , Neurofibromina 2/metabolismo , Osteosarcoma/metabolismo , Fosfoproteínas/genética , Fosfoproteínas/metabolismo , Proteínas Serina-Treonina Quinasas/metabolismo , Reacción en Cadena en Tiempo Real de la Polimerasa , Factores de Transcripción SOXB1/metabolismo , Transducción de Señal , Factores de Transcripción , Proteínas Señalizadoras YAPRESUMEN
We present DevStaR, an automated computer vision and machine learning system that provides rapid, accurate, and quantitative measurements of C. elegans embryonic viability in high-throughput (HTP) applications. A leading genetic model organism for the study of animal development and behavior, C. elegans is particularly amenable to HTP functional genomic analysis due to its small size and ease of cultivation, but the lack of efficient and quantitative methods to score phenotypes has become a major bottleneck. DevStaR addresses this challenge using a novel hierarchical object recognition machine that rapidly segments, classifies, and counts animals at each developmental stage in images of mixed-stage populations of C. elegans. Here, we describe the algorithmic design of the DevStaR system and demonstrate its performance in scoring image data acquired in HTP screens.
