Targeting MCT-1 oncogene inhibits Shc pathway and xenograft tumorigenicity

Shih, Hung-Ju; Chen, Hsiao‐Huei; Chen, Yenan; Wu, Meng-Hsun; Liou, Gunn‐Guang; Chang, Wen-Neng; Chen, Linyi; Wang, Lu‐Hai; Hsu, Hsin-Ling

doi:10.18632/oncotarget.688

Cited by 26 publications

(24 citation statements)

References 56 publications

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“…BRCA samples are shown in Fig 11a , and we see nominal statistical significance from somatic mutations in FLNB and SHC1 . FLNB is involved in vascular repair and has not been shown to be associated with cancer, but SHC1 interacts with a kinase signaling pathway that has been implicated in breast cancer [ 36 , 37 ]. Differential expression status in GRB2 , FYN , and HTT also show utility in predicting differences in survival between groups.…”

Section: Resultsmentioning

confidence: 99%

Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer

2015

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Development of high-throughput monitoring technologies enables interrogation of cancer samples at various levels of cellular activity. Capitalizing on these developments, various public efforts such as The Cancer Genome Atlas (TCGA) generate disparate omic data for large patient cohorts. As demonstrated by recent studies, these heterogeneous data sources provide the opportunity to gain insights into the molecular changes that drive cancer pathogenesis and progression. However, these insights are limited by the vast search space and as a result low statistical power to make new discoveries. In this paper, we propose methods for integrating disparate omic data using molecular interaction networks, with a view to gaining mechanistic insights into the relationship between molecular changes at different levels of cellular activity. Namely, we hypothesize that genes that play a role in cancer development and progression may be implicated by neither frequent mutation nor differential expression, and that network-based integration of mutation and differential expression data can reveal these “silent players”. For this purpose, we utilize network-propagation algorithms to simulate the information flow in the cell at a sample-specific resolution. We then use the propagated mutation and expression signals to identify genes that are not necessarily mutated or differentially expressed genes, but have an essential role in tumor development and patient outcome. We test the proposed method on breast cancer and glioblastoma multiforme data obtained from TCGA. Our results show that the proposed method can identify important proteins that are not readily revealed by molecular data, providing insights beyond what can be gleaned by analyzing different types of molecular data in isolation.

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Section: Resultsmentioning

confidence: 99%

Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer

2015

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“…27 A549, H1299 and MDA-MB231 cells were cultured in RPMI 1640 medium. 29 V5-tagged MCT-1/pLXSN, pCMV p53 and the empty vehicles (pLXSN and pCMV) were transfected into cells as previously described. 29 …”

Section: Methodsmentioning

confidence: 99%

Oncogenic MCT-1 activation promotes YY1-EGFR-MnSOD signaling and tumor progression

et al. 2017

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Tumor cells often produce high levels of reactive oxygen species (ROS) and display an increased ROS scavenging system. However, the molecular mechanism that balances antioxidative and oxidative stress in cancer cells is unclear. Here, we determined that oncogenic multiple copies in T-cell malignancy 1 (MCT-1) activity promotes the generation of intracellular ROS and mitochondrial superoxide. Overexpression of MCT-1 suppresses p53 accumulation but elevates the manganese-dependent superoxide dismutase (MnSOD) level via the YY1-EGFR signaling cascade, which protects cells against oxidative damage. Conversely, restricting ROS generation and/or targeting YY1 in lung cancer cells effectively inhibits the EGFR-MnSOD signaling pathway and cell invasiveness induced by MCT-1. Significantly, MCT-1 overexpression in lung cancer cells promotes tumor progression, necrosis and angiogenesis, and increases the number of tumor-promoting M2 macrophages and cancer-associated fibroblasts in the microenvironment. Clinical evidence further confirms that high expression of MCT-1 is associated with an increase in YY1, EGFR and MnSOD expression, accompanied by tumor recurrence, poor overall survival and EGFR mutation status in patients with lung cancers. Together, these data indicate that the MCT-1 oncogenic pathway is implicated in oxidative metabolism and lung carcinogenesis.

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“…Moreover, MCT1 overexpression is correlated with metastasis 64 . MCT1 has been used as a prognostic factor 65 , and it is thought to contribute to tumor recurrence (relapse) 66 and may mediate chemotherapy resistance too 67 . MCT1 is thought to be as a selective target in cancer 68,69 .…”

Section: Monocarboxylate Transporter 1 (Mct-1)mentioning

confidence: 99%

Tumor metabolism, cancer cell transporters, and microenvironmental resistance

Alfarouk

2016

Journal of Enzyme Inhibition and Medicinal Chemistry

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Cancer cells reprogram their metabolic machineries to enter into permanent glycolytic pathways. The full reason for such reprogramming takes place is unclear. However, this metabolic switch is not made in vain for the lactate that is generated and exported outside cells is reused by other cells. This results in the generation of a pH gradient between the low extracellular pH that is acidic (pHe) and the higher cytosolic alkaline or near neutral pH (pHi) environments that are tightly regulated by the overexpression of several pumps and ion channels (e.g. NHE-1, MCT-1, V-ATPase, CA9, and CA12). The generation of this unique pH gradient serves as a determining factor in defining ''tumor fitness''. Tumor fitness is the capacity of the tumor to invade and metastasize due to its ability to reduce the efficiency of the immune system and confer resistance to chemotherapy. In this article, we highlight the importance of tumor microenvironment in mediating the failure of chemotherapeutic agents.

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Targeting MCT-1 oncogene inhibits Shc pathway and xenograft tumorigenicity

Cited by 26 publications

References 56 publications

Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer

Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer

Oncogenic MCT-1 activation promotes YY1-EGFR-MnSOD signaling and tumor progression

Tumor metabolism, cancer cell transporters, and microenvironmental resistance

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