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1. Personalized prognostic signature for lung cancer based on 15 transcription-related gene pairs | |||
Liao Zili,Ren Zhihao,Zhang Boxiang,Zhu Ruiyu | |||
Biology 15 February 2023 | |||
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Abstract:Lung cancer is the most aggressive malignancy and the leading cause of cancer deaths worldwide. Currently, reliable biomarkers are lacking in the diagnosis, prognosis and treatment of lung cancer. Given the significant role of transcription factors in tumorigenesis and progression, we aimed to establish a signature based on transcription-related gene pairs for the first time to predict the prognosis of lung cancer patients. The gene expression data and clinical information of 1568 lung cancer patients were obtained from The Cancer Genome Atlas data portal (TCGA) and Gene Expression Omnibus (GEO) as a training cohort and validation cohort, respectively. Through univariate Cox analysis and Least Absolute Shrinkage and Selection Operator (LASSO) analysis, we screened 15 transcription-related gene pairs to construct the transcription-related prognostic signature. Based on this signature, the samples were classified into high-risk group and low-risk group. Kaplan-Meier analysis and independent prognostic analysis showed that transcription-related prognostic signature predicted overall survival in lung cancer patients (p < 0.001). Compared with multiple clinical and pathological factors, the results of multivariate Cox regression analysis indicated that the signature was an independent prognostic factor in patients with lung cancer. Further analysis revealed the cellular pathways associated with this signature and the relationship between this signature and immune cell content. In conclusion, we established for the first time the signature of transcription-related genes on prognosis as an indicator to assess the overall survival in lung cancer patients. Our study provides new ideas for developing cancer prognostic signature and discovering new drug targets. | |||
TO cite this article:Liao Zili,Ren Zhihao,Zhang Boxiang, et al. Personalized prognostic signature for lung cancer based on 15 transcription-related gene pairs[OL].[15 February 2023] http://en.paper.edu.cn/en_releasepaper/content/4759077 |
2. eQTLs weighted gene expression profiling: a trans-omics pathway expression analysis of Kashin-Beck disease | |||
Feng Zhang,Yan Wen,Xiong Guo | |||
Biology 10 October 2014 | |||
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Abstract:Pathway expression analysis is a powerful tool for pathogenetic studies of complex diseases. Kashin-Beck disease (KBD) is a serious osteoarthropathia, mainly characterized by excessive chondrocyte necrosis and apoptosis. To improve the performance of pathway expression analysis, we proposed a trans-omics expression quantitative trait loci (eQTLs) -weighted pathway expression analysis (EPEA) approach for trans-omics joint analysis of genome-wide microarray and eQTLs data. In EPEA, expression quantitative trait loci (eQTLs)-weighted Kolmogorov-Smirnov-like running sum statistic was applied for pathway enrichment analysis. Permutations are used to evaluate the significance of statistics. Using the real genome-wide microarray and eQTLs data of KBD, EPEA identified 4 apoptosis-related pathways significantly associated with KBD, including SA_PROGRAMMED_CELL_DEATH (P value = 3.7×10-3), BIOCARTA_ MITOCHONDRIA_PATHWAY (P value = 4.4×10-3), REACTOME_INTRINSIC_ PATHWAY_FOR_APOPTOSIS (P value = 6.4×10-3), ST_FAS_ SIGNALING_PATHWAY (P value = 8.9×10-3). Our results provided novel insight into the molecular mechanism underlying the excessive chondrocyte apoptosis of KBD, and illustrated the application of EPEA for joint pathway analysis of microarray and eQTLs data. A program, named EPEA was developed to implement the proposed approach. ????? | |||
TO cite this article:Feng Zhang,Yan Wen,Xiong Guo. eQTLs weighted gene expression profiling: a trans-omics pathway expression analysis of Kashin-Beck disease[OL].[10 October 2014] http://en.paper.edu.cn/en_releasepaper/content/4612734 |
3. Predicting protein submitochondrial locations by incorporating gene ontology annotations of low similarity sequences | |||
DU Pufeng | |||
Biology 15 August 2013 | |||
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Abstract:In this paper, a novel method for predicting protein submitochondrial locations was proposed. In this method, the concept of extended gene ontology supporting set was proposed. A new scoreing schem, which is called the over-represented gene ontology score, was proposed. This method achieved better performance than state-of-the-art methods. | |||
TO cite this article:DU Pufeng. Predicting protein submitochondrial locations by incorporating gene ontology annotations of low similarity sequences[OL].[15 August 2013] http://en.paper.edu.cn/en_releasepaper/content/4555493 |
4. Estimates of Minimum Amount of Suitable Habitat and Management of Aphid, Parasitoid and Hyperparasitoid in Wheat Field | |||
Zhao Zihua ,He Dahan ,Zhao Yingshu ,Hang Jia ,Shi Xiangfeng | |||
Biology 29 March 2010 | |||
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Abstract:Minimum Area of Suitable Habitat (MASH) and Minimun Viable Population (MVP) were two important aspects in Population Viability Analysis (PVA). MASH for a viable population can be estimated in several ways. The density-area method estimated MASH as the smallest area in which population can survival for a long time and variation was below 0.05. We used a variant of density-area method to study MASH for aphids, parasitoids, and hyperparasitoids in Northwest of China, where wheat was a main crop in agriculture. The variant was based on the premise that individuals within populations were likely to occur at usually high densities variation when confined to small areas and it estimated MASH as the smallest area beyond which density plateaus. For all 72 sites, aphids, parasitoids and hyperparasitoids occurred in all sites because wheat fields were highly homogeneous. We found that a consistant inverse density-area relationship was present over smaller areas, but different species had different function, especially in different trophic level. MASH of M. avenae, S. graminum, A. avenae, A. gifuensis, A. sp.1 and P. aphidis estimated from density-area relationship were 260, 240, 510, 490, 950, and 990m2 respectially. Results of inverse proportion function according to which MASH of M. avenae, S. graminum, A. avenae, A. gifuensis, A. sp.1 and P. aphidis were 310, 286, 543, 492, 952, and 1003 m2 respectially were similar to that of density-area relationship. We concluded that a negative density-area relationship may be an inevitable consequence of agricultural intensification and farmland fragmentation. We also concluded that different species may have different MASH requirement in agricultural landscape according to body size, migration, trophic level, and habitat quality, which could interpret the phenomenon that highest percent parasitism was always in 800-1000 m2 wheat fields which exceeded MASH of parasitoids and suppressed activity of hyperparasitoids . Finally, we concluded that the value of any MASH as a pest control tool was compromised in Conservation Biological Control (CBC). | |||
TO cite this article:Zhao Zihua ,He Dahan ,Zhao Yingshu , et al. Estimates of Minimum Amount of Suitable Habitat and Management of Aphid, Parasitoid and Hyperparasitoid in Wheat Field[OL].[29 March 2010] http://en.paper.edu.cn/en_releasepaper/content/41250 |
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