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1.
Mol Carcinog ; 63(8): 1467-1485, 2024 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-38726928

RESUMEN

Reactive oxygen species (ROS) are metabolic by-products of cells, and abnormal changes in their levels are often associated with tumor development. Our aim was to determine the role of collagen and calcium binding EGF domain 1 (CCBE1) in oxidative stress and tumorigenesis in non-small cell lung cancer cells (NSCLC). We investigated the tumorigenic potential of CCBE1 in NSCLC using in vitro and in vivo models of CCBE1 overexpression and knockdown. Immunohistochemical staining results showed that the expression of CCBE1 in cancer tissues was significantly higher than that in adjacent tissues. Cell counting Kit 8, clonal formation, wound healing, and transwell experiments showed that CCBE1 gene knockdown significantly inhibited the migration, invasion, and proliferation of NSCLC cell lines. In terms of mechanism, the silencing of CCBE1 can significantly promote the morphological abnormalities of mitochondria, significantly increase the intracellular ROS level, and promote cell apoptosis. This change of oxidative stress can affect cell proliferation, migration, and invasion by regulating the phosphorylation level of ERK/JNK/P38 MAPK. Specifically, the downregulation of CCBE1 inhibits the phosphorylation of ERK/P38 and promotes the phosphorylation of JNK in NSCLC, and this regulation can be reversed by the antioxidant NAC. In vivo experiments confirmed that downregulating CCBE1 gene could inhibit the growth of NSCLC in BALB/c nude mice. Taken together, our results confirm the tumorigenic role of CCBE1 in promoting tumor invasion and migration in NSCLC, and reveal the molecular mechanism by which CCBE1 regulates oxidative stress and the ERK/JNK/P38 MAPK pathway.


Asunto(s)
Proteínas de Unión al Calcio , Carcinoma de Pulmón de Células no Pequeñas , Movimiento Celular , Proliferación Celular , Neoplasias Pulmonares , Sistema de Señalización de MAP Quinasas , Especies Reactivas de Oxígeno , Humanos , Especies Reactivas de Oxígeno/metabolismo , Carcinoma de Pulmón de Células no Pequeñas/metabolismo , Carcinoma de Pulmón de Células no Pequeñas/patología , Carcinoma de Pulmón de Células no Pequeñas/genética , Animales , Neoplasias Pulmonares/metabolismo , Neoplasias Pulmonares/patología , Neoplasias Pulmonares/genética , Ratones , Proteínas de Unión al Calcio/metabolismo , Proteínas de Unión al Calcio/genética , Fosforilación , Línea Celular Tumoral , Apoptosis , Ratones Desnudos , Proteínas Quinasas p38 Activadas por Mitógenos/metabolismo , Masculino , Regulación Neoplásica de la Expresión Génica , Progresión de la Enfermedad , Femenino , Estrés Oxidativo , Ratones Endogámicos BALB C
2.
Transl Lung Cancer Res ; 10(2): 866-877, 2021 Feb.
Artículo en Inglés | MEDLINE | ID: mdl-33718028

RESUMEN

BACKGROUND: We aim to establish neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) related nomograms based on the clinical data and peripheral blood markers to predict the survivals of patients with limited-stage small-cell lung cancer (LS-SCLC). METHODS: A total of 299 LS-SCLC patients after surgery were enrolled in this study. Univariate and multivariate analyses were conducted to select independent prognostic factors to develop the nomograms and then subjected to bootstrap internal validation. The optimal cutoff value of NLR and PLR before surgery was calculated by X-tile (version 3.6.1) and the overall survival (OS) was analyzed by Kaplan-Meier method and compared by log-rank test. RESULTS: According to the X-tile calculation, the NLR value and PLR cutoff values are 2.6 and 156.7, respectively. The prognosis of patients with elevated NLR or PLR value was significantly worse than patients with lower NLR (HR =1.798, 95% CI: 1.284-2.518, P=0.001) or PLR (HR =1.781, 95% CI: 1.318-2.407, P<0.001) value. Two Nomograms were developed according to the two multivariate cox regression models based on NLR and PLR. Concordance index (C-index) curves and calibration curves show that the two models have a better effect in predicting prognosis. At the same time, compared with the tumor node metastasis (TNM) staging system, our models also show better accuracy and stability. CONCLUSIONS: Elevated NLR and PLR predict poor prognosis in their respective nomograms in patients with LS-SCLC.

3.
DNA Cell Biol ; 38(5): 423-435, 2019 May.
Artículo en Inglés | MEDLINE | ID: mdl-30864845

RESUMEN

The Qianhua Mutton Merino (QHMM) is a new variety of sheep (Ovis aries) with improved meat performance compared with the traditional Small Tail Han (STH) sheep variety. We recently reported the transcriptome profiling of longissimus muscle tissues between QHMM and STH sheep. In the present study, we aimed to evaluate key micro (mi)RNA-mRNA networks associated with sheep muscle growth and development. We used miRNA sequencing to obtain longissimus muscle miRNA profiles from QHMM and STH sheep. We identified a total of 153 known sheep miRNAs, of which 4 were differentially expressed (DE) between the 2 sheep varieties. We combined these results with mRNA library data to build an miRNA-mRNA network, including 26 target genes of the 4 DE miRNAs. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that 26 target genes were significantly enriched in 86 biological processes, including muscle organogenesis, myoblast migration, cell proliferation, and adipose tissue development, and in 9 metabolic pathways, including carbohydrate, nucleotide, and amino acid metabolic pathways. oar-miR-655-3p and its target gene ACSM3 and oar-miR-381-5p and its target gene ABAT were selected for subsequent analysis based on GO and KEGG analyses. The binding sites of oar-miR-655-3p with ACSM3 and oar-miR-381-5p with ABAT were validated by a dual-luciferase reporter gene detection system. This represents the first integrative analysis of miRNA-mRNA networks in QHMM and STH muscles and suggests that DE miRNAs, especially oar-miR-655-3p and oar-miR-381-5p, play crucial roles in muscle growth and development.


Asunto(s)
Biomarcadores/análisis , Redes Reguladoras de Genes , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , MicroARNs/genética , Músculo Esquelético/metabolismo , ARN Mensajero/genética , Análisis de Secuencia de ARN/métodos , Animales , Biología Computacional , Femenino , Perfilación de la Expresión Génica , Ovinos
4.
Naturwissenschaften ; 104(9-10): 84, 2017 Sep 25.
Artículo en Inglés | MEDLINE | ID: mdl-28948304

RESUMEN

Testis development and spermatogenesis are vital factors that influence male animal fertility. In order to identify spermatogenesis-related genes and further provide a theory basis for finding biomarkers related to male sheep fertility, 2-, 6-, and 12-month-old Small Tail Han Sheep testes were selected to investigate the dynamic changes of sheep testis development. Hematoxylin-eosin routine staining and RNA-Seq technique were used to perform histological and transcriptome analysis for these testes. The results showed that 630, 102, and 322 differentially expressed genes (DEGs) were identified in 2- vs 6-month-old, 6- vs 12-month-old, and 2- vs 12-month-old testes, respectively. GO and KEGG analysis showed the following: DEGs in 2- vs 6-month-old testes were mainly related to the GO terms of sexual maturation and the pathways of multiple metabolism and biosynthesis; in 6- vs 12-month-old testes, most of the GO terms that DEGs involved in were related to metabolism and translation processes; the most significantly enriched pathway is the ribosome pathway. The union of DEGs in 2- vs 6-month-old, 6- vs 12-month-old, and 2- vs 12-month-old testes was categorized into eight profiles by series cluster. Subsequently, the eight profiles were classified into four model profiles and four co-expression networks were constructed based on the DEGs in these model profiles. Finally, 29 key regulatory genes related to spermatogenesis were identified in the four co-expression networks. The expression of 13 DEGs (CA3, APOH, MYOC, CATSPER4, SYT6, SERPINA10, DAZL, ADIPOR2, RAB13, CEP41, SPAG4, ODF1, and FRG1) was validated by RT-PCR.


Asunto(s)
Espermatogénesis , Testículo , Animales , Perfilación de la Expresión Génica , Masculino , Maduración Sexual , Ovinos , Transcriptoma
5.
Sci Rep ; 6: 33586, 2016 09 20.
Artículo en Inglés | MEDLINE | ID: mdl-27645777

RESUMEN

The Qianhua Mutton Merino (QHMM) is a new sheep (Ovis aries) variety with better meat performance compared with the traditional local variety Small Tail Han (STH) sheep. We aimed to evaluate the transcriptome regulators associated with muscle growth and development between the QHMM and STH. We used RNA-Seq to obtain the transcriptome profiles of the longissimus muscle from the QHMM and STH. The results showed that 960 genes were differentially expressed (405 were up-regulated and 555 were down-regulated). Among these, 463 differently expressed genes (DEGs) were probably associated with muscle growth and development and were involved in biological processes such as skeletal muscle tissue development and muscle cell differentiation; molecular functions such as catalytic activity and oxidoreductase activity; cellular components such as mitochondrion and sarcoplasmic reticulum; and pathways such as metabolic pathways and citrate cycle. From the potential genes, a gene-act-network and co-expression-network closely related to muscle growth and development were identified and established. Finally, the expressions of nine genes were validated by real-time PCR. The results suggested that some DEGs, including MRFs, GXP1 and STAC3, play crucial roles in muscle growth and development processes. This genome-wide transcriptome analysis of QHMM and STH muscle is reported for the first time.


Asunto(s)
Perfilación de la Expresión Génica , Músculo Esquelético/metabolismo , Ovinos/genética , Transcriptoma , Animales , Biología Computacional/métodos , Calidad de los Alimentos , Regulación de la Expresión Génica , Ontología de Genes , Redes Reguladoras de Genes , Secuenciación de Nucleótidos de Alto Rendimiento , Carne , Fenotipo , Carácter Cuantitativo Heredable , Reproducibilidad de los Resultados , Análisis de Secuencia de ARN
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