UPP2

Last update 08 May 2025

Basic Info

Synonyms

UDRPASE2, UP2, UPase 2

+ [4]

Introduction

Catalyzes the reversible phosphorylytic cleavage of uridine to uracil and ribose-1-phosphate which can then be utilized as carbon and energy sources or in the rescue of pyrimidine bases for nucleotide synthesis (PubMed:12849978, PubMed:21855639). Shows broad substrate specificity and can also accept deoxyuridine and other analogous compounds (PubMed:12849978).

100 Clinical Results associated with UPP2

100 Translational Medicine associated with UPP2

0 Patents (Medical) associated with UPP2

Literatures (Medical) associated with UPP2

01 May 2025·Poultry Science

Identification of key genes associated with residual feed intake in small-sized meat ducks through integrated analysis of mRNA and miRNA transcriptomes

Article

Author: Jiang, Yong ; Li, Xiaofan ; Guo, Qixin ; Geng, Dandan ; Chen, Guohong ; Yuan, Chunyou ; Bai, Hao ; Chang, Guobin ; Wang, Zhixiu ; Wang, Chenxiao

As a major producer and consumer of duck meat, China faces industry challenges due to low feed conversion efficiency. Residual feed intake (RFI), a key metric for poultry feed utilization, remains poorly characterized in small-sized meat ducks. We raised 1,000 ducklings with similar initial body weight (BW) under controlled conditions until 63 days of age. RFI was calculated using average daily gain (ADG), average daily feed intake (ADFI), and metabolic body weight (MBW^0.75). Thirty high-RFI (HRFI) and thirty low-RFI (LRFI) ducks were selected to evaluate growth performance. Hypothalamic samples from 6 HRFI and 6 LRFI ducks underwent transcriptomic analysis, including differential gene expression, gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway analysis, weighted gene co-expression network analysis, and miRNA target prediction. Results showed that the LRFI group had significantly lower feed intake (FI) and ADFI than the HRFI group (P < 0.05). Compared to low RFI controls, HRFI meat ducks exhibited 45 differentially expressed (DE) miRNAs (6 upregulated and 39 downregulated) and 323 DE mRNAs (133 upregulated and 190 downregulated), enriched in substance and energy metabolism pathways. Weighted gene co-expression network analysis identified ten hub DE miRNAs, including miR-1-3p, miR-10-5p/3p, miR-182-5p/3p, miR-183-5p, miR-263-5p, miR-96-5p, miR-7, and novel-m0108-5p. miRNA-mRNA network analysis revealed 43 DE regulatory pairs, including 15 with negative feedback. Notably, miR-182 targeted and regulated the highest number of DE mRNAs, showing negative feedback interactions with DDC, UPP2, PRSS35, and SLCO1C1. Dual-luciferase reporter assays confirmed the binding of partial genes. Given DDC's role in dopamine and serotonin synthesis, we further validated the miR-182-5p/DDC regulatory relationship through overexpression, interference, and Western blot experiments. This study provides novel insights into the molecular mechanisms underlying feed efficiency in ducks.

01 Feb 2025·Cancer Medicine

Transcriptomic Profiles for Elucidating Response of Bladder Intracavitary Hyperthermic Perfusion Chemotherapy in High‐Risk Nonmuscular Invasive Bladder Cancer

Article

Author: Wan, Pei ; Zou, Wenchao ; Pan, Jinghua ; Jiang, Huiming ; Jiang, Linjun ; Liu, Qinghua ; Chen, Nanhui ; Peng, Ying ; Zhang, Tianhui ; Zhang, Guihao ; Huang, Zhicheng

ABSTRACTBackgroundBladder intracavitary hyperthermic perfusion chemotherapy (HIPEC) is a promising treatment for non‐muscular invasive bladder cancer (NMIBC). However, the molecular mechanisms underlying the response to HIPEC remain poorly understood. This study aimed to elucidate the transcriptomic profiles associated with the response to HIPEC in NMIBC patients.MethodsRNA sequencing was performed on bladder tumor samples from NMIBC patients who underwent HIPEC treatment. Differentially expressed genes (DEGs) between responders and non‐responders to HIPEC were identified. Gene ontology and pathway analysis were conducted to explore the biological functions and pathways enriched in the DEGs. Additionally, the expression of specific immune‐related genes was evaluated for their association with HIPEC response. The diagnostic efficiency of selected genes in predicting relapse before and after HIPEC treatment was assessed in a validation cohort.ResultsWe assessed the expression status of differentially expressed genes (DEGs) between responders and non‐responders to HIPEC. Gene ontology and pathway analysis revealed that DEGs were enriched in immune‐related pathways, including cytokine‐cytokine receptor interaction, chemokine signaling pathway, and antigen processing and presentation. Furthermore, the expression of several immune‐related genes, including ZMAP4, UPP2, and GALR1, was significantly associated with the response to HIPEC. Therefore, the immune system's reaction plays a crucial role in the response to HIPEC in patients with NMIBC. At last, a considerable diagnostic efficiency that tissue TMEFF2, KRT222, and GTSF1 in predicting relapse in NMIBC patients after HIPEC treatment, and ZMAP4, UPP2, and GALR1 in predicting relapse in NMIBC patients before HIPEC treatment in the validation cohort.ConclusionTranscriptomic profiling revealed that immune‐related pathways and genes play a crucial role in the response to HIPEC in NMIBC patients. These findings suggest that transcriptomic profiling could provide a valuable tool for predicting treatment outcomes and identifying therapeutic targets for NMIBC.

01 Jun 2024·Biochemical Genetics

Mongolian HCC vs. Caucasian HCC: The Metabolic Reprogramming Process in Mongolian HCC is an Interesting Difference

Article

Author: Xie, Xiaofeng ; Huang, Rui ; Hai, Xiangjun ; Song, Lei ; Zhang, Zejuan ; Yang, Kun ; Dong, Kaizhong

Racial/ethnic and region disparities in incidence and mortality are obviously in liver cancer. Mongolia has the highest reported incidence and mortality of hepatocellular carcinoma (HCC) in the world, while the incidence of HCC is relatively low in the United States, but differences in their molecular characteristics remain largely elusive. Here we report differentially expressed genes (DEGs) in Mongolian hepatocellular carcinoma and in Caucasian HCC and their intersection DEGs, as well as their corresponding signaling pathways in Mongolian and Caucasian hepatocellular carcinoma patients based on the transcriptome sequences from Gene Expression Omnibus (GEO) database. We got 908 up-regulated genes and 1946 down-regulated genes in Mongolian HCC, 1244 up-regulated genes and 1912 down-regulated genes in Caucasian HCC, 254 Co-upregulated genes and 1035 co-downregulated genes in Mongolian and Caucasian. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that most of the genes with altered expression levels in Mongolian HCC participate in biological processes that involve metabolic reprogramming of various substances, accounting for about one-third of all biological processes. In particular, multiple amino acid biosynthesis and metabolic processes appear to be specific in Mongolian HCC compared with Caucasian HCC. The biological processes they share include those in which most immune cells are involved and cell cycle-related biological processes. In addition, we also found the genes UPP2, PCK1, GLYAT, GNMT, ADH1B and HPD, encode for key metabolic enzymes, whose expression level up-regulated or down-regulated more than 5 times in Mongolian HCC and was dramatically correlated with survival in Mongolian HCC (p value < 0.01), More importantly, these molecules are potential targets for some metabolic antitumor drugs. This study not only makes up for the shortcomings of previous studies on liver cancer, which paid more attention to its commonality, but ignored the specificity of liver cancer in different races and regions. More importantly, the purpose of this study is to identify robust molecular subclasses and information with underlying unique tumor biology. And this study may have important implications for the study of the pathogenic factors and molecular mechanisms of hepatocellular carcinoma and the precise therapy of Mongolian HCC.

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UPP2

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