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Dong M, Li P, Luo J, Chen B, Jiang H. Oligopeptide/Histidine Transporter PHT1 and PHT2 - Function, Regulation, and Pathophysiological Implications Specifically in Immunoregulation. Pharm Res 2023; 40:2585-2596. [PMID: 37610621 DOI: 10.1007/s11095-023-03589-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Accepted: 08/15/2023] [Indexed: 08/24/2023]
Abstract
The oligopeptide/histidine transporters PHT1 and PHT2, two mammalian solute carrier family 15A proteins, mediate the transmembrane transport of histidine and some di/tripeptides via proton gradient. PHT1 and PHT2 are distributed in a variety of tissues but are preferentially expressed in immune cells and localize to the lysosome-related organelles. Studies have reported the relationships between PHT1/PHT2 and immune diseases. PHT1 and PHT2 participate in the regulation of lysosomal homeostasis and lysosome-associated signaling pathways through their transport and nontransport functions, playing important roles in inflammatory diseases. In this review, we summarize recent research on PHT1 and PHT2, aiming to provide reference for their further biological research and as targets for drug design.
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Affiliation(s)
- Minlei Dong
- Institute of Drug Metabolism and Pharmaceutical Analysis, Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Ping Li
- Department of Clinical Pharmacy, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jun Luo
- Institute of Drug Metabolism and Pharmaceutical Analysis, Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Binxin Chen
- Institute of Drug Metabolism and Pharmaceutical Analysis, Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Huidi Jiang
- Institute of Drug Metabolism and Pharmaceutical Analysis, Zhejiang Province Key Laboratory of Anti-Cancer Drug Research, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
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Zangene E, Marashi SA, Montazeri H. SL-scan identifies synthetic lethal interactions in cancer using metabolic networks. Sci Rep 2023; 13:15763. [PMID: 37737478 PMCID: PMC10516981 DOI: 10.1038/s41598-023-42992-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 09/18/2023] [Indexed: 09/23/2023] Open
Abstract
Exploiting synthetic lethality is a promising strategy for developing targeted cancer therapies. However, identifying clinically significant synthetic lethal (SL) interactions among a large number of gene combinations is a challenging computational task. In this study, we developed the SL-scan pipeline based on metabolic network modeling to discover SL interaction. The SL-scan pipeline identifies the association between simulated Flux Balance Analysis knockout scores and mutation data across cancer cell lines and predicts putative SL interactions. We assessed the concordance of the SL pairs predicted by SL-scan with those of obtained from analysis of the CRISPR, shRNA, and PRISM datasets. Our results demonstrate that the SL-scan pipeline outperformed existing SL prediction approaches based on metabolic networks in identifying SL pairs in various cancers. This study emphasizes the importance of integrating multiple data sources, particularly mutation data, when identifying SL pairs for targeted cancer therapies. The findings of this study may lead to the development of novel targeted cancer therapies.
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Affiliation(s)
- Ehsan Zangene
- Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran
| | - Sayed-Amir Marashi
- Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran.
| | - Hesam Montazeri
- Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
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Zhu J, Mou Y, Ye S, Hu H, Wang R, Yang Q, Hu Y. Identification of a Six-Gene SLC Family Signature With Prognostic Value in Patients With Lung Adenocarcinoma. Front Cell Dev Biol 2022; 9:803198. [PMID: 34977043 PMCID: PMC8714960 DOI: 10.3389/fcell.2021.803198] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 11/30/2021] [Indexed: 12/17/2022] Open
Abstract
Given the importance of solute carrier (SLC) proteins in maintaining cellular metabolic homeostasis and that their dysregulation contributes to cancer progression, here we constructed a robust SLC family signature for lung adenocarcinoma (LUAD) patient stratification. Transcriptomic profiles and relevant clinical information of LUAD patients were downloaded from the TCGA and GEO databases. SLC family genes differentially expressed between LUAD tissues and adjacent normal tissues were identified using limma in R. Of these, prognosis-related SLC family genes were further screened out and used to construct a novel SLC family-based signature in the training cohort. The accuracy of the prognostic signature was assessed in the testing cohort, the entire cohort, and the external GSE72094 cohort. Correlations between the prognostic signature and the tumor immune microenvironment and immune cell infiltrates were further explored. We found that seventy percent of SLC family genes (279/397) were differentially expressed between LUAC tissues and adjacent normal. Twenty-six genes with p-values < 0.05 in univariate Cox regression analysis and Kaplan-Meier survival analysis were regarded as prognosis-related SLC family genes, six of which were used to construct a prognostic signature for patient classification into high- and low-risk groups. Kaplan-Meier survival analysis in all internal and external cohorts revealed a better overall survival for patients in the low-risk group than those in the high-risk group. Univariate and multivariate Cox regression analyses indicated that the derived risk score was an independent prognostic factor for LUAD patients. Moreover, a nomogram based on the six-gene signature and clinicopathological factors was developed for clinical application. High-risk patients had lower stromal, immune, and ESTIMATE scores and higher tumor purities than those in the low-risk group. The proportions of infiltrating naive CD4 T cells, activated memory CD4 T cells, M0 macrophages, resting dendritic cells, resting mast cells, activated mast cells, and eosinophils were significantly different between the high- and low-risk prognostic groups. In all, the six-gene SLC family signature is of satisfactory accuracy and generalizability for predicting overall survival in patients with LUAD. Furthermore, this prognostics signature is related to tumor immune status and distinct immune cell infiltrates in the tumor microenvironment.
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Affiliation(s)
- Jing Zhu
- Department of Respiratory and Critical Care Medicine, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yong Mou
- Department of Respiratory and Critical Care Medicine, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shenglan Ye
- Department of Respiratory and Critical Care Medicine, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongling Hu
- Department of Respiratory and Critical Care Medicine, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Rujuan Wang
- Department of Respiratory and Critical Care Medicine, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qing Yang
- Department of Respiratory and Critical Care Medicine, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Hu
- Department of Respiratory and Critical Care Medicine, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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