Transposon insertional mutagenesis in mice identifies human breast cancer susceptibility genes and signatures for stratification

Chen, Liming; Jenjaroenpun, Piroon; Pillai, Andrea Mun Ching; Ivshina, Anna V.; Ow, Ghim Siong; Motakis, Efthymios; Tang, Ziyang; Tan, Tuan Zea; Lee, Song-Choon; Rogers, Keith; Ward, Jerrold M.; Mori, Seiichi; Adams, David J.; Jenkins, Nancy A.; Copeland, Neal G.; Ban, Kenneth H K; Kuznetsov, Vladimir A.; Thiery, Jean Paul

doi:10.1073/pnas.1701512114

Cited by 42 publications

(51 citation statements)

References 87 publications

(114 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…TRPS1 expression is also elevated in luminal breast cancer as compared with basal breast cancer (14), which contains more CSC population than luminal breast cancer (15). Mutations in TRPS1 have been reported in basal-like breast cancer (16,17). However, whether and how TRPS1 contributes to CSC functions and tumor initiation by regulating SOX2 expression is mostly unknown.…”

mentioning

confidence: 99%

Transcriptional repressor GATA binding 1–mediated repression of SRY-box 2 expression suppresses cancer stem cell functions and tumor initiation

Gong

et al. 2018

Journal of Biological Chemistry

Self Cite

View full text Add to dashboard Cite

Edited by Xiao-Fan Wang Cancer stem cells (CSCs) have been reported in a variety of cancers. SRY-box 2 (SOX2) is a member of the SOX family of transcription factors and has been shown to play a critical role in maintaining the functions of CSCs and promoting tumor initiation. However, the underlying mechanisms for the transcriptional regulation of the SOX2 gene in CSCs are unclear. In this study, using in silico and experimental approaches, we identified transcriptional repressor GATA binding 1 (TRPS1), an atypical GATA-type transcription factor, as a critical transcriptional regulator that represses SOX2 expression and thereby suppresses cancer stemness and tumorigenesis. Mechanistically, TRPS1 repressed SOX2 expression by directly targeting the consensus GATA-binding element in the SOX2 promoter as elucidated by ChIP and luciferase reporter assays. Of note, in vitro mammosphere formation assays in culture and in vivo xenograft tumor initiation experiments in mouse models revealed that TRPS1-mediated repression of SOX2 expression suppresses CSC functions and tumor initiation. Taken together, our study provides detailed mechanistic insights into CSC functions and tumor initiation by the TRPS1-SOX2 axis. Cancer stem cells (CSCs) 2 are at the root of tumor recurrence and metastasis in many human cancers (1). Numerous studies have shown the important role of SRY-box 2 (SOX2) in CSC

show abstract

mentioning

confidence: 99%

Transcriptional repressor GATA binding 1–mediated repression of SRY-box 2 expression suppresses cancer stem cell functions and tumor initiation

Gong

et al. 2018

Journal of Biological Chemistry

Self Cite

View full text Add to dashboard Cite

show abstract

“…Eleven of the 12 sites were differentially edited including AZIN1 S367G , highlighting the importance of AZIN1 RNA editing in cancer development. The top 3 edited genes were NOP14 I779V (chr4:2,938,299), FLNB M2324V (chr3: 58,156,064), and IGFBP7 K95R (chr4: 57,110,068), all of which have been suggested to suppress breast cancer progression (26)(27)(28). Moreover, DNA mutations of NOP14 I779V and FLNB M2324V are reported in COSMIC (29), demonstrating the utility of TCEA to identify driver-like editing events in carcinogenesis.…”

Section: Edcancer Modulementioning

confidence: 95%

The Cancer Editome Atlas: A Resource for Exploratory Analysis of the Adenosine-to-Inosine RNA Editome in Cancer

Lin

Chen

2019

Cancer Research

View full text Add to dashboard Cite

Increasing evidence has suggested a role for adenosine-toinosine RNA editing in carcinogenesis. However, the clinical utility of RNA editing remains limited because functions of the vast majority of editing events remain largely unexplored. To help the cancer research community investigate functional consequences of individual editing events, we have developed a user-friendly bioinformatic resource, The Cancer Editome Atlas (TCEA; http://tcea.tmu.edu.tw). TCEA characterizes >192 million editing events at >4.6 million editing sites from approximately 11,000 samples across 33 cancer types in The Cancer Genome Atlas. Clinical information, miRNA expression , and alteration in miRNA targeting modulated through RNA editing are also integrated into TCEA. TCEA supports several modules to search, analyze, and visualize the cancer editome, providing a solid basis for investigating the oncogenic mechanisms of RNA editing and expediting the identification of therapeutic targets in cancer. Significance: This user-friendly bioinformatic resource reduces the barrier to analyzing the huge and complex cancer RNA editome that cancer researchers face and facilitates the identification of novel therapeutic targets in cancer.

show abstract

“…Following 1-D DDg, the input file is used to obtain the statistical voting stratification of a patient from the grouping information generated using the binary variables. For each patient, the SWVg score is calculated based on an optimized number of statistically weighted votes of the binary variables (Chen et al, 2017). The estimated SWVg score cut-off was determined by maximizing the significance of the patient separation into HR and LR subgroups.…”

Section: Statistical and Bioinformatics Analysesmentioning

confidence: 99%

“…S1). However, such gene classifications are useful and often correlated with the functional classification of many known tumor suppressors and oncogenes, which are respectively defined based on the pathobiological roles of the genes and gene products in malignant cells (Chen et al, 2017).…”

Section: Identification Of Common Prognostic Genes In Pt and At Samplmentioning

confidence: 99%

Tumor‐adjacent tissue co‐expression profile analysis reveals pro‐oncogenic ribosomal gene signature for prognosis of resectable hepatocellular carcinoma

et al. 2017

View full text Add to dashboard Cite

Currently, molecular markers are not used when determining the prognosis and treatment strategy for patients with hepatocellular carcinoma (HCC). In the present study, we proposed that the identification of common pro‐oncogenic pathways in primary tumors (PT) and adjacent non‐malignant tissues (AT) typically used to predict HCC patient risks may result in HCC biomarker discovery. We examined the genome‐wide mRNA expression profiles of paired PT and AT samples from 321 HCC patients. The workflow integrated differentially expressed gene selection, gene ontology enrichment, computational classification, survival predictions, image analysis and experimental validation methods. We developed a 24‐ribosomal gene‐based HCC classifier (RGC), which is prognostically significant in both PT and AT. The RGC gene overexpression in PT was associated with a poor prognosis in the training (hazard ratio = 8.2, P = 9.4 × 10−6) and cross‐cohort validation (hazard ratio = 2.63, P = 0.004) datasets. The multivariate survival analysis demonstrated the significant and independent prognostic value of the RGC. The RGC displayed a significant prognostic value in AT of the training (hazard ratio = 5.0, P = 0.03) and cross‐validation (hazard ratio = 1.9, P = 0.03) HCC groups, confirming the accuracy and robustness of the RGC. Our experimental and bioinformatics analyses suggested a key role for c‐MYC in the pro‐oncogenic pattern of ribosomal biogenesis co‐regulation in PT and AT. Microarray, quantitative RT‐PCR and quantitative immunohistochemical studies of the PT showed that DKK1 in PT is the perspective biomarker for poor HCC outcomes. The common co‐transcriptional pattern of ribosome biogenesis genes in PT and AT from HCC patients suggests a new scalable prognostic system, as supported by the model of tumor‐like metabolic redirection/assimilation in non‐malignant AT. The RGC, comprising 24 ribosomal genes, is introduced as a robust and reproducible prognostic model for stratifying HCC patient risks. The adjacent non‐malignant liver tissue alone, or in combination with HCC tissue biopsy, could be an important target for developing predictive and monitoring strategies, as well as evidence‐based therapeutic interventions, that aim to reduce the risk of post‐surgery relapse in HCC patients.

show abstract

Transposon insertional mutagenesis in mice identifies human breast cancer susceptibility genes and signatures for stratification

Cited by 42 publications

References 87 publications

Transcriptional repressor GATA binding 1–mediated repression of SRY-box 2 expression suppresses cancer stem cell functions and tumor initiation

Transcriptional repressor GATA binding 1–mediated repression of SRY-box 2 expression suppresses cancer stem cell functions and tumor initiation

The Cancer Editome Atlas: A Resource for Exploratory Analysis of the Adenosine-to-Inosine RNA Editome in Cancer

Tumor‐adjacent tissue co‐expression profile analysis reveals pro‐oncogenic ribosomal gene signature for prognosis of resectable hepatocellular carcinoma

Contact Info

Product

Resources

About