A Pharmacogenomic Landscape in Human Liver Cancers

Qiu, Zhixin; Li, Hong; Zhang, Zhengtao; Zhu, Zhenfeng; He, Sheng; Wang, Xujun; Wang, Pengcheng; Qin, Jianjie; Zhuang, Liping; Wang, Wei; Xie, Fei; Gu, Ying; Zou, Keke; Li, Chao; Li, Chun; Wang, Chenhua; Cen, Jin; Chen, Xiaotao; Shu, Yajing; Zhao, Zhigang; Lu, Hui; Min, Lihua; Fu, Yong; Huang, Xiaowu; Lv, Hui; Zhou, He; Ji, Yuan; Zhang, Zhigang; Meng, Zhiqiang; Shi, Xiaolei; Zhang, Haibin; Li, Yixue; Hui, Lijian

doi:10.1016/j.ccell.2019.07.001

Cited by 158 publications

(139 citation statements)

References 85 publications

(118 reference statements)

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“…(40) It was therefore surprising that mTOR inhibition did not significantly alter HCC viability in the setting of purine synthesis inhibition, consistent with a previous report showing a mode of PI3K regulation of purine synthesis independent of mTOR/S6 kinase in mouse embryonic fibroblasts and C2C12 myoblasts. (41) In the context of HCC, a recent study comparing the responses of 81 HCC cell lines to a panel of anticancer drugs demonstrated that, despite rapamycin and PI-103 eliciting similar sensitivities in many lines, a significant fraction exhibited opposing vulnerabilities to PI3K or mTOR inhibition, (31) attesting to a subset of HCC wherein mTOR is dispensable for PI3K regulation. Here, we demonstrate that PI3K signaling modulates E2F1 occupancy on purine synthetic gene promoters through RB phosphorylation, thus relieving sequestration of E2F1 to RB, consistent with a role for E2F1 in regulating the cell cycle and metabolic adaptations of cancer cells.…”

Section: Discussionmentioning

confidence: 99%

“…HCCs exhibit extensive heterogeneity with regards to proteomic, metabolomics, and immune profiles as well as responses to anticancer drugs, contributing to different metabolic requirements across tumors. (31,32) We hypothesized that every tumor would thus have a unique growth dependency on IMPDH-driven purine biosynthesis and demonstrate varying sensitivities and tolerance toward MPA. PDX mouse models offer a clinically relevant system to test this hypothesis, with drug studies being able to be performed in vivo as well as in vitro on PDX organoids in the context of heterogeneous molecular alterations in patients.…”

Section: Heterogeneity In Purine Synthetic Pathway Activity Determinementioning

confidence: 99%

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Targeted Inhibition of Purine Metabolism Is Effective in Suppressing Hepatocellular Carcinoma Progression

et al. 2020

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We demonstrate that in human HCCs with deregulated expression of purine metabolic enzymes, targeting purine metabolism was effective in blocking tumor cell proliferation, leading to tumor shrinkage. Precise regulation of purine metabolic activity was coordinated by the activation status of a PI3K‐E2F1 axis, and potent suppression of purine metabolism via combinatorial targeting of PI3K and the purine synthetic rate‐limiting enzyme IMPDH resulted in enhanced efficacy in a pre‐clinical model. These data provide a strong basis for future precision‐medicine focused clinical trials targeting this tumor‐specific metabolic adaptation as a point of vulnerability in patients with HCC.

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Section: Discussionmentioning

confidence: 99%

Section: Heterogeneity In Purine Synthetic Pathway Activity Determinementioning

confidence: 99%

Targeted Inhibition of Purine Metabolism Is Effective in Suppressing Hepatocellular Carcinoma Progression

et al. 2020

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“…Biological and clinical heterogeneity among otherwise histologically indistinguishable tumors explains the vast majority of therapeutic failures and provides the major rationale for individualizing, or "personalizing", cancer treatment. Thus far, the means of attaining such precision medicine-based goals has involved a combination of improved clinical staging; high-resolution imaging techniques; immuno-histochemical-based tumor sub-classification and, increasingly, molecular and pharmacogenomic evaluation to stratify individuals according to inherent risk and likelihood of response to chemotherapeutic regimens [5,[25][26][27][28][29][30][31][32][33][34][35][36][37][38]. The deployment of newer techniques such as liquid biopsies, which quantify circulating tumor DNA, promise to provide additional benefits by allowing serial assessments of response to therapy or the detection of impending recurrence in cases where the tumor has been previously resected or otherwise rendered undetectable by standard methods [39][40][41][42].…”

Section: Discussionmentioning

confidence: 99%

Sequential analysis of transcript expression patterns improves survival prediction in multiple cancers

2020

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Background: Long-term survival in numerous cancers often correlates with specific whole transcriptome profiles or the expression patterns of smaller numbers of transcripts. In some instances, these are better predictors of survival than are standard classification methods such as clinical stage or hormone receptor status in breast cancer. Here, we have used the method of "t-distributed stochastic neighbor embedding" (t-SNE) to show that, collectively, the expression patterns of small numbers of functionally-related transcripts from fifteen cancer pathways correlate with long-term survival in the vast majority of tumor types from The Cancer Genome Atlas (TCGA). We then ask whether the sequential application of t-SNE using the transcripts from a second pathway improves predictive capability or whether t-SNE can be used to refine the initial predictive power of whole transcriptome profiling. Methods: RNAseq data from 10,227 tumors in TCGA were previously analyzed using t-SNE-based clustering of 362 transcripts comprising 15 distinct cancer-related pathways. After showing that certain clusters were associated with differential survival, each relevant cluster was re-analyzed by t-SNE with a second pathway's transcripts. Alternatively, groups with differential survival identified by whole transcriptome profiling were subject to a second, t-SNE-based analysis. Results: Sequential analyses employing either t-SNE➔t-SNE or whole transcriptome profiling➔t-SNE analyses were in many cases superior to either individual method at predicting long-term survival. We developed a dynamic and intuitive R Shiny web application to explore the t-SNE based transcriptome clustering and survival analysis across all TCGA cancers and all 15 cancer-related pathways in this analysis. This application provides a simple interface to select specific t-SNE clusters and analyze survival predictability using both individual or sequential approaches. The user can recreate the relationships described in this analysis and further explore many different cancer, pathway, and cluster combinations. Non-R users can access the application on the web at https://chpupsom19.shinyapps.io/ Survival_Analysis_tsne_umap_TCGA. The application, R scripts performing survival analysis, and t-SNE clustering results of TCGA expression data can be accessed on GitHub enabling users to download and run the application locally with ease (https://github.com/RavulaPitt/Sequential-t-SNE/).

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“…However, due to the majority of patients were diagnosed at an advanced clinical stage, especially in Eastern Asia and sub-Saharan Africa, cancer-speci c mortality still continues to climb [3]. Substantial advances have been made to understand the detail mechanism of tumor transformation and HCC progression [4,5]. Accumulating ndings of factors contributing to the development of targeted drugs, systemic therapy for HCC patients has made great progress [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…Substantial advances have been made to understand the detail mechanism of tumor transformation and HCC progression [4,5]. Accumulating ndings of factors contributing to the development of targeted drugs, systemic therapy for HCC patients has made great progress [4,5].…”

Section: Introductionmentioning

confidence: 99%

TRAIP functions as an oncogene in hepatocellular carcinoma via Rb/EZH2/p21 signaling pathway

Luo¹,

Li²,

Zhang³

et al. 2020

Preprint

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Background The TRAF-interacting protein (TRAIP) has been identified as a master regulator of DNA damage and implicated in the progression of human cancers. Yet the underlying mechanism of TRAIP-mediated malignant phenotype remains unclear. Methods The expression of TRAIP in hepatocellular carcinoma (HCC) was examined by qRT-PCR, western blot and immunohistochemistry. The clinical significance of TRAIP was determined by Kaplan-Meier survival analyses. The biological function and the underlying mechanism of TRAIP in HCC progression were investigated, using cellular and molecular biological experiments.Results Here, we show that TRAIP is upregulated in HCC and functions as an oncogene via Rb/EZH2/p21 signaling. Overexpression of TRAIP, at both mRNA and protein levels, is correlated with more aggressive clinicopathological features, and unfavorable overall and disease-free survivals. In vitro experiments demonstrate that ectopic expression of TRAIP enhances, whereas knockdown of TRAIP attenuates HCC cell proliferation. Further data show that TRAIP interacts with SPAG5 in HCC cells, which results in the stabilization of TRAIP protein. TRAIP overexpression suppresses the expression of Rb, subsequently leading to the increase of EZH2 and decrease of p21. Re-expression of Rb and p21 significantly inhibits TRAIP-mediated cell growth. Conclusion Collectively, our findings suggest TRAIP exert oncogenic activity and have prognostic and therapeutic potential in HCC.

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A Pharmacogenomic Landscape in Human Liver Cancers

Cited by 158 publications

References 85 publications

Targeted Inhibition of Purine Metabolism Is Effective in Suppressing Hepatocellular Carcinoma Progression

Targeted Inhibition of Purine Metabolism Is Effective in Suppressing Hepatocellular Carcinoma Progression

Sequential analysis of transcript expression patterns improves survival prediction in multiple cancers

TRAIP functions as an oncogene in hepatocellular carcinoma via Rb/EZH2/p21 signaling pathway

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