Programmed cell death 10 promotes metastasis and epithelial-mesenchymal transition of hepatocellular carcinoma via PP2Ac-mediated YAP activation

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Abstract

Tumour metastasis is the main cause of postoperative tumour recurrence and mortality in patients with hepatocellular carcinoma (HCC), but the underlying mechanism remains unclear. Accumulating evidence has demonstrated that programmed cell death 10 (PDCD10) plays an important role in many biological processes. However, the role of PDCD10 in HCC progression is still elusive. In this study, we aimed to explore the clinical significance and molecular function of PDCD10 in HCC. PDCD10 is significantly upregulated in HCC, which also correlates with aggressive clinicopathological characteristics and predicts poor prognosis of HCC patients after liver resection. High PDCD10 expression promotes HCC cell proliferation, migration, and invasion in vitro and tumour growth, metastasis in vivo. In addition, PDCD10 could facilitate epithelial-to-mesenchymal transition (EMT) of HCC cells. In terms of the mechanism, PDCD10 directly binds to the catalytic subunit of protein phosphatase 2A (PP2Ac) and increases its enzymatic activity, leading to the interaction of YAP and dephosphorylation of the YAP protein. This interaction contributes to YAP nuclear translocation and transcriptional activation. PP2Ac is necessary for PDCD10-mediated HCC progression. Knocking down PP2Ac abolished the tumour-promoting role of PDCD10 in the migration, invasion and EMT of HCC. Moreover, a PP2Ac inhibitor (LB100) could restrict tumour growth and metastasis of HCC with high PDCD10 expression. Collectively, PDCD10 promotes EMT and the progression of HCC by interacting with PP2Ac to promote YAP activation, which provides new insight into the mechanism of cancer metastasis. PDCD10 may be a potential prognostic biomarker and therapeutic target for HCC.

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Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

Ahmedin Jemal, Lindsey A Torre, Rebecca Siegel … (2018)

This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.

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Douglas Hanahan, Robert A. Weinberg (2011)

The hallmarks of cancer comprise six biological capabilities acquired during the multistep development of human tumors. The hallmarks constitute an organizing principle for rationalizing the complexities of neoplastic disease. They include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis. Underlying these hallmarks are genome instability, which generates the genetic diversity that expedites their acquisition, and inflammation, which fosters multiple hallmark functions. Conceptual progress in the last decade has added two emerging hallmarks of potential generality to this list-reprogramming of energy metabolism and evading immune destruction. In addition to cancer cells, tumors exhibit another dimension of complexity: they contain a repertoire of recruited, ostensibly normal cells that contribute to the acquisition of hallmark traits by creating the "tumor microenvironment." Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer. Copyright © 2011 Elsevier Inc. All rights reserved.

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clusterProfiler: an R package for comparing biological themes among gene clusters.

Guangchuang Yu, Li-Gen Wang, Yanyan Han … (2012)

Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.