The miR-200 family and miR-205 regulate epithelial to mesenchymal transition by targeting ZEB1 and SIP1

Gregory, Philip A.; Bert, Andrew G.; Paterson, Emily; Barry, Simon C.; Tsykin, Anna; Farshid, Gelareh; Vadas, Mathew A.; Khew‐Goodall, Yeesim; Goodall, Gregory J.

doi:10.1038/ncb1722

Cited by 3,486 publications

(3,515 citation statements)

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“…EMT facilitates tissue remodeling in embryonic development and is an essential early step in tumor metastasizing. [35][36][37] Several oncogenic microRNAs are expressed in early stages of development in undifferentiated embryonic cells. However, their expression decreases in differentiated tissue, whereas the opposite holds true for tumor suppressive microRNAs.…”

Section: Discussionmentioning

confidence: 99%

MicroRNA expression profiles associated with pancreatic adenocarcinoma and ampullary adenocarcinoma

Schultz

Werner

Willenbrock³

et al. 2012

Modern Pathology

137

106

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MicroRNAs have potential as diagnostic cancer biomarkers. The aim of this study was (1) to define microRNA expression patterns in formalin-fixed parafin-embedded tissue from pancreatic ductal adenocarcinoma, ampullary adenocarcinoma, normal pancreas and chronic pancreatitis without using micro-dissection and (2) to discover new diagnostic microRNAs and combinations of microRNAs in cancer tissue. The expression of 664 microRNAs in tissue from 170 pancreatic adenocarcinomas and 107 ampullary adenocarcinomas were analyzed using a commercial microRNA assay. Results were compared with chronic pancreatitis, normal pancreas and duodenal adenocarcinoma. In all, 43 microRNAs had higher and 41 microRNAs reduced expression in pancreatic cancer compared with normal pancreas. In all, 32 microRNAs were differently expressed in pancreatic adenocarcinoma compared with chronic pancreatitis (17 higher; 15 reduced). Several of these microRNAs have not before been related to diagnosis of pancreatic cancer (eg, miR-492, miR-614, miR-622). MiR-614, miR-492, miR-622, miR-135b* and miR-196 were most differently expressed. MicroRNA profiles of pancreatic and ampullary adenocarcinomas were correlated (0.990). MicroRNA expression profiles for pancreatic cancer described in the literature were consistent with our findings, and the microRNA profile for pancreatic adenocarcinoma (miR-196b-miR-217) was validated. We identified a more significant expression profile, the difference between miR-411 and miR-198 (P ¼ 2.06 Â 10 À 54 ) and a diagnostic LASSO classifier using 19 microRNAs (sensitivity 98.5%; positive predictive value 97.8%; accuracy 97.0%). We also identified microRNA profiles to subclassify ampullary adenocarcinomas into pancreatobiliary or intestinal type. In conclusion, we found that combinations of two microRNAs could roughly separate neoplastic from nonneoplastic samples. A diagnostic 19 microRNA classifier was constructed which without micro-dissection could discriminate pancreatic and ampullary adenocarcinomas from chronic pancreatitis and normal pancreas with high sensitivity and accuracy. Ongoing prospective studies will evaluate if these microRNA profiles are useful on fine-needle biopsies for early diagnosis of pancreatic cancer. Modern Pathology (2012Pathology ( ) 25, 1609Pathology ( -1622 doi:10.1038/modpathol.2012; published online 10 August 2012Keywords: ampullary adenocarcinoma; chronic pancreatitis; microRNA; normal pancreas; pancreatic adenocarcinoma; pancreatic cancer Pancreatic cancer is the fourth most common cause of cancer death in United States and Europe. 1,2 Less than 20% of the patients can be operated with curative intent and the 5-year survival after surgery is below 20%. 3 Early diagnosis is difficult and the clinical and histological similarities between pancreatic cancer and chronic pancreatitis further complicate the differentiation between inflammation and cancer.

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Section: Discussionmentioning

confidence: 99%

MicroRNA expression profiles associated with pancreatic adenocarcinoma and ampullary adenocarcinoma

Schultz

Werner

Willenbrock³

et al. 2012

Modern Pathology

137

106

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“…26,33 Branching points in the tree ('nodes') separate between groups of tissues that show substantial differences in specific microRNAs, and these are ostensibly related to underlying biological differences. A representative example of this is the use of hsa-miR-200c, involved in epithelial-to-mesenchymal transition, 16,17 to identify tumors of epithelial tissue origin from tumors of non-epithelial origin (Figure 1; node #5 in Figure 2). Using this method, we selected a list of 48 microRNAs that contained highly useful information for tissue classification.…”

Section: Tissue Classification By Microrna Qrt-pcrmentioning

confidence: 99%

“…This classification was traced back to node #1, the branching point where lung and liver origins diverge (Figure 2). This node uses hsamiR-122, a well-known marker of hepatic cells, 20,[34][35][36] together with hsa-miR-200c, an established epithelial marker, 16,17,26 two microRNAs that have been previously shown to identify hepatic from non-hepatic malignancies. 26,35 The expression of these microRNAs in this sample, in particular the very high expression of hsa-miR-122 (Figure 4a), are strong indicators of a possible hepatic origin of this sample.…”

Section: Classification Examplementioning

confidence: 99%

“…[8][9][10][11][12] Most studies of molecular diagnosis of tissue of origin used messenger RNA (mRNA) profiling of tumor samples. 8,[13][14][15] MicroRNAs, 21-23-nucleotide-long functional RNAs, have an important function in tissue differentiation 16,17 and tumorigenesis, 18,19 and have highly tissue-specific expression patterns. [20][21][22] The unique expression profiles of microRNAs characteristic of each tissue and the malignancies arising in them can permit their accurate identification.…”

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Validation of a microRNA-based qRT-PCR test for accurate identification of tumor tissue origin

et al. 2010

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Identification of the tissue of origin of a tumor is vital to its management. Previous studies showed tissuespecific expression patterns of microRNA and suggested that microRNA profiling would be useful in addressing this diagnostic challenge. MicroRNAs are well preserved in formalin-fixed, paraffin-embedded (FFPE) samples, further supporting this approach. To develop a standardized assay for identification of the tissue origin of FFPE tumor samples, we used microarray data from 504 tumor samples to select a shortlist of 104 microRNA biomarker candidates. These 104 microRNAs were profiled by proprietary quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) on 356 FFPE tumor samples. A total of 48 microRNAs were chosen from this list of candidates and used to train a classifier. We developed a clinical test for the identification of the tumor tissue of origin based on a standardized protocol and defined the classification criteria. The test measures expression levels of 48 microRNAs by qRT-PCR, and predicts the tissue of origin among 25 possible classes, corresponding to 17 distinct tissues and organs. The biologically motivated classifier combines the predictions generated by a binary decision tree and K-nearest neighbors (KNN). The classifier was validated on an independent, blinded set of 204 FFPE tumor samples, including nearly 100 metastatic tumor samples. The test predictions correctly identified the reference diagnosis in 85% of the cases. In 66% of the cases the two algorithm predictions (tree and KNN) agreed on a single-tissue origin, which was identical to the reference diagnosis in 90% of cases. Thus, a qRT-PCR test based on the expression profile of 48 tissue-specific microRNAs allows accurate identification of the tumor tissue of origin.

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“…These Smad complexes translocate into the nucleus where they regulate the transcription of various target genes in cooperation with other transcription factors. While expression of ZEB1 and ZEB2 is suppressed by epithelial miR‐200 family of miRNA (Gregory et al ., 2008), TGF‐β induces their expression in addition to some other EMT‐related transcription factors, including Snail, and Slug, in certain types of normal and cancer cells (Gregory et al ., 2011; Heldin et al ., 2012; Miyazono et al ., 2012; Xu et al ., 2009). …”

Section: Introductionmentioning

confidence: 99%

ZEB1‐regulated inflammatory phenotype in breast cancer cells

et al. 2017

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Zinc finger E‐box binding protein 1 (ZEB1) and ZEB2 induce epithelial‐mesenchymal transition (EMT) and enhance cancer progression. However, the global view of transcriptional regulation by ZEB1 and ZEB2 is yet to be elucidated. Here, we identified a ZEB1‐regulated inflammatory phenotype in breast cancer cells using chromatin immunoprecipitation sequencing and RNA sequencing, followed by gene set enrichment analysis (GSEA) of ZEB1‐bound genes. Knockdown of ZEB1 and/or ZEB2 resulted in the downregulation of genes encoding inflammatory cytokines related to poor prognosis in patients with cancer, including IL6 and IL8, therefore suggesting that ZEB1 and ZEB2 have similar functions in terms of the regulation of production of inflammatory cytokines. Antibody array and ELISA experiments confirmed that ZEB1 controlled the production of the IL‐6 and IL‐8 proteins. The secretory proteins regulated by ZEB1 enhanced breast cancer cell proliferation and tumor growth. ZEB1 expression in breast cancer cells also affected the growth of fibroblasts in cell culture, and the accumulation of myeloid‐derived suppressor cells in tumors in vivo. These findings provide insight into the role of ZEB1 in the progression of cancer, mediated by inflammatory cytokines, along with the initiation of EMT.

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The miR-200 family and miR-205 regulate epithelial to mesenchymal transition by targeting ZEB1 and SIP1

Cited by 3,486 publications

References 34 publications

MicroRNA expression profiles associated with pancreatic adenocarcinoma and ampullary adenocarcinoma

MicroRNA expression profiles associated with pancreatic adenocarcinoma and ampullary adenocarcinoma

Validation of a microRNA-based qRT-PCR test for accurate identification of tumor tissue origin

ZEB1‐regulated inflammatory phenotype in breast cancer cells

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