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A microRNA DNA methylation signature for human cancer metastasis.

ABSTRACT: MicroRNAs (miRNAs) are small, noncoding RNAs that can contribute to cancer development and progression by acting as oncogenes or tumor suppressor genes. Recent studies have also linked different sets of miRNAs to metastasis through either the promotion or suppression of this malignant process. Interestingly, epigenetic silencing of miRNAs with tumor suppressor features by CpG island hypermethylation is also emerging as a common hallmark of human tumors. Thus, we wondered whether there was a miRNA hypermethylation profile characteristic of human metastasis. We used a pharmacological and genomic approach to reveal this aberrant epigenetic silencing program by treating lymph node metastatic cancer cells with a DNA demethylating agent followed by hybridization to an expression microarray. Among the miRNAs that were reactivated upon drug treatment, miR-148a, miR-34b/c, and miR-9 were found to undergo specific hypermethylation-associated silencing in cancer cells compared with normal tissues. The reintroduction of miR-148a and miR-34b/c in cancer cells with epigenetic inactivation inhibited their motility, reduced tumor growth, and inhibited metastasis formation in xenograft models, with an associated down-regulation of the miRNA oncogenic target genes, such as C-MYC, E2F3, CDK6, and TGIF2. Most important, the involvement of miR-148a, miR-34b/c, and miR-9 hypermethylation in metastasis formation was also suggested in human primary malignancies (n = 207) because it was significantly associated with the appearance of lymph node metastasis. Our findings indicate that DNA methylation-associated silencing of tumor suppressor miRNAs contributes to the development of human cancer metastasis.

SUBMITTER: Lujambio A

PROVIDER: S-EPMC2528872 | biostudies-literature | 2008 Sep

REPOSITORIES: biostudies-literature

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A microRNA DNA methylation signature for human cancer metastasis.

Lujambio Amaia A Calin George A GA Villanueva Alberto A Ropero Santiago S Sánchez-Céspedes Montserrat M Blanco David D Montuenga Luis M LM Rossi Simona S Nicoloso Milena S MS Faller William J WJ Gallagher William M WM Eccles Suzanne A SA Croce Carlo M CM Esteller Manel M

Proceedings of the National Academy of Sciences of the United States of America 20080903 36

MicroRNAs (miRNAs) are small, noncoding RNAs that can contribute to cancer development and progression by acting as oncogenes or tumor suppressor genes. Recent studies have also linked different sets of miRNAs to metastasis through either the promotion or suppression of this malignant process. Interestingly, epigenetic silencing of miRNAs with tumor suppressor features by CpG island hypermethylation is also emerging as a common hallmark of human tumors. Thus, we wondered whether there was a miRN ...[more]

PMID: 18768788

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Project description:Distant metastasis is the major cause of mortality in colorectal cancer (CRC). We performed a systemic, comprehensive discovery for expression patterns of metastasis-specific microRNAs (miRNAs) by directly comparing primary CRCs (pCRCs) and matched liver metastases (LMs) and evaluated the feasibility of their clinical application as metastasis-specific biomarkers. CRC metastasis-specific miRNA profiles were generated by analyzing nine pairs of pCRC and LM tissues, followed by quantitative validation in an independent cohort of 58 pairs of matched pCRC and LM tissues. We evaluated associations between miRNA expression and patient survival and ability to predict metastasis in another 84 patients with CRC. Subsequently, associations were quantitatively validated in 175 CRC tissues and 169 serum samples. Kaplan-Meier, Cox regression, and logistic regression analyses were used. All statistical tests were two-sided. Twenty-three miRNAs were identified that were differentially expressed between pCRC and LM (P < .001; FDR < .5). Four miRNAs downregulated in LM (let-7i, miR-10b, miR-221, and miR-320a) and one upregulated miR (miR-885-5p) were quantitatively validated in pCRC (P < .0001). Low let-7i expression in pCRC tissue predicted worsened prognosis (hazard ratio [HR] = 5.0, 95% confidence interval [CI] = 1.0 to 24.4, P = .0479) as well as distant metastasis (odds ratio [OR] = 5.5, 95% CI = 1.1 to 26.8, P = .0334). High miR-10b expression in pCRC tissue independently predicted distant metastasis (OR = 4.9, 95% CI = 1.2 to 19.7, P = .0248). High serum miR-885-5p expression independently predicted prognosis (HR = 2.9, 95% CI = 1.1 to 7.5, P = .0323), LN metastasis (OR = 3.0, 95% CI = 1.3 to 7.2, P = .0116), and distant metastasis (OR = 3.1, 95% CI = 1.0 to 10.0, P = .0456), whereas tissue miR-885-5p expression did not. Expression patterns of miRNAs were confirmed by in situ hybridization. We discovered a metastasis-specific miRNA signature in pCRCs and discovered novel tissue- and serum-based CRC metastasis-specific miRNA biomarkers through intensive validation. These unique miRNAs may be clinically applicable to predict prognosis and distant metastasis in CRC.

Project description:BackgroundLymph node metastasis (LNM) is an important factor for both treatment and prognosis of early gastric cancer (EGC). Current methods are insufficient to evaluate LNM in EGC due to suboptimal accuracy. Herein, we aim to identify methylation signatures for LNM of EGC, facilitate precision diagnosis, and guide treatment modalities.MethodsFor marker discovery, genome-wide methylation sequencing was performed in a cohort (marker discovery) using 47 fresh frozen (FF) tissue samples. The identified signatures were subsequently characterized for model development using formalin-fixed paraffin-embedded (FFPE) samples by qPCR assay in a second cohort (model development cohort, n = 302, training set: n = 151, test set: n = 151). The performance of the established model was further validated using FFPE samples in a third cohorts (validation cohort, n = 130) and compared with image-based diagnostics, conventional clinicopathology-based model (conventional model), and current standard workups.ResultsFifty LNM-specific methylation signatures were identified de novo and technically validated. A derived 3-marker methylation model for LNM diagnosis was established that achieved an AUC of 0.87 and 0.88, corresponding to the specificity of 80.9% and 85.7%, sensitivity of 80.6% and 78.1%, and accuracy of 80.8% and 83.8% in the test set of model development cohort and validation cohort, respectively. Notably, this methylation model outperformed computed tomography (CT)-based imaging with a superior AUC (0.88 vs. 0.57, p < 0.0001) and individual clinicopathological features in the validation cohort. The model integrated with clinicopathological features demonstrated further enhanced AUCs of 0.89 in the same cohort. The 3-marker methylation model and integrated model reduced 39.4% and 41.5% overtreatment as compared to standard workups, respectively.ConclusionsA novel 3-marker methylation model was established and validated that shows diagnostic potential to identify LNM in EGC patients and thus reduce unnecessary gastrectomy in EGC.

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A microRNA DNA methylation signature for human cancer metastasis.

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A microRNA DNA methylation signature for human cancer metastasis.

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