Identification of a microRNA signature associated with risk of distant metastasis in nasopharyngeal carcinoma

Purpose Despite significant improvement in locoregional control in the contemporary era of nasopharyngeal carcinoma (NPC) treatment, patients still suffer from a significant risk of distant metastasis (DM). Identifying those patients at risk of DM would aid in personalized treatment in the future. MicroRNAs (miRNAs) play many important roles in human cancers; hence, we proceeded to address the primary hypothesis that there is a miRNA expression signature capable of predicting DM for NPC patients. Methods and results The expression of 734 miRNAs was measured in 125 (Training) and 121 (Validation) clinically annotated NPC diagnostic biopsy samples. A 4-miRNA expression signature associated with risk of developing DM was identified by fitting a penalized Cox Proportion Hazard regression model to the Training data set (HR 8.25; p < 0.001), and subsequently validated in an independent Validation set (HR 3.2; p = 0.01). Pathway enrichment analysis indicated that the targets of miRNAs associated with DM appear to be converging on cell-cycle pathways. Conclusions This 4-miRNA signature adds to the prognostic value of the current “gold standard” of TNM staging. In-depth interrogation of these 4-miRNAs will provide important biological insights that could facilitate the discovery and development of novel molecularly targeted therapies to improve outcome for future NPC patients.

[1]  A. Dreher Modeling Survival Data Extending The Cox Model , 2016 .

[2]  K. Oda,et al.  Cyclin-Dependent Kinase 4/6–Specific Activities as a Biomarker for Prognosis and Chemosensitivity in Endometrial Cancer , 2014 .

[3]  Chien-Feng Li,et al.  Cyclin-dependent kinase 4 overexpression is mostly independent of gene amplification and constitutes an independent prognosticator for nasopharyngeal carcinoma , 2014, Tumor Biology.

[4]  Huiling Yang,et al.  Nuclear expression of CDK4 correlates with disease progression and poor prognosis in human nasopharyngeal carcinoma , 2014, Histopathology.

[5]  Hsien-Da Huang,et al.  miRTarBase update 2014: an information resource for experimentally validated miRNA-target interactions , 2013, Nucleic Acids Res..

[6]  R. Seiler,et al.  CCND1/CyclinD1 status in metastasizing bladder cancer: a prognosticator and predictor of chemotherapeutic response , 2014, Modern Pathology.

[7]  Ying Sun,et al.  Progress report of a randomized trial comparing long‐term survival and late toxicity of concurrent chemoradiotherapy with adjuvant chemotherapy versus radiotherapy alone in patients with stage III to IVB nasopharyngeal carcinoma from endemic regions of China , 2013, Cancer.

[8]  Benjamin Haibe-Kains,et al.  Significance Analysis of Prognostic Signatures , 2013, PLoS Comput. Biol..

[9]  T. Lam,et al.  The battle against nasopharyngeal cancer. , 2012, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[10]  Ying Sun,et al.  Prognostic value of a microRNA signature in nasopharyngeal carcinoma: a microRNA expression analysis. , 2012, The Lancet. Oncology.

[11]  C. Croce,et al.  microRNA involvement in human cancer. , 2012, Carcinogenesis.

[12]  U. Pastorino,et al.  Role of MicroRNAs in Lung Cancer: MicroRNA Signatures in Cancer Prognosis , 2012, Cancer journal.

[13]  A. King,et al.  A phase II study of concurrent cetuximab-cisplatin and intensity-modulated radiotherapy in locoregionally advanced nasopharyngeal carcinoma. , 2012, Annals of oncology : official journal of the European Society for Medical Oncology.

[14]  Paul C. Boutros,et al.  NanoStringNorm: an extensible R package for the pre-processing of NanoString mRNA and miRNA data , 2012, Bioinform..

[15]  John P A Ioannidis,et al.  Clinical outcome prediction by microRNAs in human cancer: a systematic review. , 2012, Journal of the National Cancer Institute.

[16]  M. Tsai,et al.  Association of cyclin D1 genotypes with nasopharyngeal carcinoma risk. , 2012, Anticancer research.

[17]  Wei Zhang,et al.  Concurrent chemoradiotherapy versus radiotherapy alone for locoregionally advanced nasopharyngeal carcinoma. , 2012, Asian Pacific journal of cancer prevention : APJCP.

[18]  Ching-Yin Ho,et al.  Post-treatment late complications of nasopharyngeal carcinoma , 2012, European Archives of Oto-Rhino-Laryngology.

[19]  H. Adami,et al.  Eight-signature classifier for prediction of nasopharyngeal [corrected] carcinoma survival. , 2011, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[20]  David Venet,et al.  Most Random Gene Expression Signatures Are Significantly Associated with Breast Cancer Outcome , 2011, PLoS Comput. Biol..

[21]  Jorge S Reis-Filho,et al.  Microarrays in the 2010s: the contribution of microarray-based gene expression profiling to breast cancer classification, prognostication and prediction , 2011, Breast Cancer Research.

[22]  Edith A Perez,et al.  MicroRNA signatures: clinical biomarkers for the diagnosis and treatment of breast cancer. , 2011, Trends in molecular medicine.

[23]  J. Goeman L1 Penalized Estimation in the Cox Proportional Hazards Model , 2009, Biometrical journal. Biometrische Zeitschrift.

[24]  Igor Jurisica,et al.  Prognostic gene signatures for non-small-cell lung cancer , 2009, Proceedings of the National Academy of Sciences.

[25]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.

[26]  T. Mok,et al.  A phase II study of patients with metastatic or locoregionally recurrent nasopharyngeal carcinoma and evaluation of plasma Epstein–Barr virus DNA as a biomarker of efficacy , 2008, Cancer Chemotherapy and Pharmacology.

[27]  E. Brambilla,et al.  E2F-1, Skp2 and cyclin E oncoproteins are upregulated and directly correlated in high-grade neuroendocrine lung tumors , 2007, Oncogene.

[28]  Y. Maitani,et al.  Non-viral delivery of the connexin 43 gene with histone deacetylase inhibitor to human nasopharyngeal tumor cells enhances gene expression and inhibits in vivo tumor growth. , 2007, International journal of oncology.

[29]  Charles E McCulloch,et al.  Relaxing the rule of ten events per variable in logistic and Cox regression. , 2007, American journal of epidemiology.

[30]  S. Leung,et al.  Plasma Epstein-Barr viral deoxyribonucleic acid quantitation complements tumor-node-metastasis staging prognostication in nasopharyngeal carcinoma. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[31]  C. Croce,et al.  MicroRNA signatures in human cancers , 2006, Nature Reviews Cancer.

[32]  B. O'Sullivan,et al.  Prognostic Significance of the Epstein-Barr Virus, p53, Bcl-2, and Survivin in Nasopharyngeal Cancer , 2006, Clinical Cancer Research.

[33]  W. Kuo,et al.  Array-based comparative genomic hybridization analysis identified cyclin D1 as a target oncogene at 11q13.3 in nasopharyngeal carcinoma. , 2005, Cancer research.

[34]  J. Whang‐Peng,et al.  Multicenter, phase II study of cetuximab in combination with carboplatin in patients with recurrent or metastatic nasopharyngeal carcinoma. , 2005, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[35]  Yau-Huei Wei,et al.  Quantification of plasma Epstein-Barr virus DNA in patients with advanced nasopharyngeal carcinoma. , 2004, The New England journal of medicine.

[36]  Rick Chappell,et al.  Primary tumor volume of nasopharyngeal carcinoma: prognostic significance for local control. , 2004, International journal of radiation oncology, biology, physics.

[37]  J. Sham,et al.  Prognostic value of epidermal growth factor receptor expression in patients with advanced stage nasopharyngeal carcinoma treated with induction chemotherapy and radiotherapy. , 2004, International journal of radiation oncology, biology, physics.

[38]  Patrick Royston,et al.  A new measure of prognostic separation in survival data , 2004, Statistics in medicine.

[39]  Young-Duck Kim,et al.  E2F1 Expression is Related with the Poor Survival of Lymph Node-positive Breast Cancer Patients Treated with Fluorouracil, Doxorubicin and Cyclophosphamide , 2003, Breast Cancer Research and Treatment.

[40]  F. Kondo,et al.  Expression of transcription factor E2F-1 in pancreatic ductal carcinoma: an immunohistochemical study. , 2003, Pathology, research and practice.

[41]  Ø. Langsrud,et al.  50–50 multivariate analysis of variance for collinear responses , 2002 .

[42]  Martin Vingron,et al.  Variance stabilization applied to microarray data calibration and to the quantification of differential expression , 2002, ISMB.

[43]  P. Grambsch,et al.  Modeling Survival Data: Extending the Cox Model , 2000 .

[44]  K. To,et al.  High resolution allelotype of microdissected primary nasopharyngeal carcinoma. , 2000, Cancer research.

[45]  T. Lumley,et al.  Time‐Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker , 2000, Biometrics.

[46]  R. Tibshirani The lasso method for variable selection in the Cox model. , 1997, Statistics in medicine.

[47]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[48]  V. Ambros,et al.  The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14 , 1993, Cell.