The BRCA1/2-directed miRNA signature predicts a good prognosis in ovarian cancer patients with wild-type BRCA1/2

Ovarian cancer patients carrying alterations (i.e., germline mutations, somatic mutations, hypermethylations and/or deletions) of BRCA1 or BRCA2 (BRCA1/2) have a better prognosis than BRCA1/2 alteration non-carriers. However, patients with wild-type BRCA1/2 may also have a favorable prognosis as a result of other mechanisms that remain poorly elucidated, such as the deregulation of miRNAs. We therefore sought to identify BRCA1/2-directed miRNA signatures that have prognostic value in ovarian cancer patients with wild-type BRCA1/2 and study how the deregulation of miRNAs impacts the prognosis of patients treated with platinum-based chemotherapy. By analyzing multidimensional datasets of ovarian cancer patients from the TCGA data portal, we identified three miRNAs (hsa-miR-146a, hsa-miR-148a and hsa-miR-545) that target BRCA1/2 and were associated with overall survival and progression-free survival in patients with wild-type BRCA1/2. By analyzing the expression profiles and Gene Ontology functional enrichment, we found that carriers of BRCA1/2 alterations and patients with miRNA deregulation shared a common mechanism, regulation of the DNA repair-related pathways, that affects the prognosis of ovarian cancer patients. Our work highlights that a proportion of patients with wild-type BRCA1/2 ovarian cancers benefit from platinum-based chemotherapy and that the patients who benefit could be predicted from BRCA1/2-directed miRNA signature.

[1]  Rochelle L. Garcia,et al.  Molecular Cancer Methylation and Protein Expression of Dna Repair Genes: Association with Chemotherapy Exposure and Survival in Sporadic Ovarian and Peritoneal Carcinomas , 2022 .

[2]  R. Lidereau,et al.  Down-regulation of BRCA1 expression by miR-146a and miR-146b-5p in triple negative sporadic breast cancers , 2011, EMBO molecular medicine.

[3]  S. Shen,et al.  MicroRNA-25 expression level is an independent prognostic factor in epithelial ovarian cancer , 2014, Clinical and Translational Oncology.

[4]  Anjali J. Koppal,et al.  Supplementary data: Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites , 2010 .

[5]  Chi-Ying F. Huang,et al.  miRTarBase: a database curates experimentally validated microRNA–target interactions , 2010, Nucleic Acids Res..

[6]  Ana Kozomara,et al.  miRBase: integrating microRNA annotation and deep-sequencing data , 2010, Nucleic Acids Res..

[7]  J. Brenton,et al.  Evolution of platinum resistance in high-grade serous ovarian cancer. , 2011, The Lancet. Oncology.

[8]  C. Croce,et al.  microRNAs: Master regulators as potential therapeutics in cancer. , 2011, Annual review of pharmacology and toxicology.

[9]  Xiang Du,et al.  The long non-coding RNAs, a new cancer diagnostic and therapeutic gold mine , 2013, Modern Pathology.

[10]  A. D’Andrea,et al.  A DNA Repair Pathway–Focused Score for Prediction of Outcomes in Ovarian Cancer Treated With Platinum-Based Chemotherapy , 2012, Journal of the National Cancer Institute.

[11]  Zheng Guo,et al.  Separate enrichment analysis of pathways for up- and downregulated genes , 2014, Journal of The Royal Society Interface.

[12]  Gord Glendon,et al.  Association Between BRCA1 and BRCA2 Mutations and Survival in Women With Invasive Epithelial Ovarian Cancer , 2012 .

[13]  I. Jacobs,et al.  BRCA1 and BRCA2 Mutation Prevalence and Clinical Characteristics of a Population-Based Series of Ovarian Cancer Cases from Denmark , 2008, Clinical Cancer Research.

[14]  Chenguang Wang,et al.  Network analysis of genomic alteration profiles reveals co-altered functional modules and driver genes for glioblastoma. , 2013, Molecular bioSystems.

[15]  B. Martínez-Delgado,et al.  The miR-200 family controls beta-tubulin III expression and is associated with paclitaxel-based treatment response and progression-free survival in ovarian cancer patients. , 2010, Endocrine-Related Cancer.

[16]  C. Creighton,et al.  High-grade serous ovarian cancer arises from fallopian tube in a mouse model , 2012, Proceedings of the National Academy of Sciences.

[17]  D. Matei,et al.  Olaparib maintenance therapy in platinum-sensitive relapsed ovarian cancer. , 2012, The New England journal of medicine.

[18]  Martin Reczko,et al.  DIANA-microT web server v5.0: service integration into miRNA functional analysis workflows , 2013, Nucleic Acids Res..

[19]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[20]  A. Jemal,et al.  Cancer Statistics, 2010 , 2010, CA: a cancer journal for clinicians.

[21]  S. Powell,et al.  BRCA1 and BRCA2: different roles in a common pathway of genome protection , 2011, Nature Reviews Cancer.

[22]  E. Orlandi,et al.  The role of miRNAs in mast cells and other innate immune cells , 2013, Immunological reviews.

[23]  K. Hess,et al.  Association of BRCA1 and BRCA2 mutations with survival, chemotherapy sensitivity, and gene mutator phenotype in patients with ovarian cancer. , 2011, JAMA.

[24]  Michael Kertesz,et al.  The role of site accessibility in microRNA target recognition , 2007, Nature Genetics.

[25]  N. Dubrawsky.  Cancer statistics , 1989, CA: a cancer journal for clinicians.

[26]  K. Kelnar,et al.  The microRNA miR-34a inhibits prostate cancer stem cells and metastasis by directly repressing CD44. , 2011, Nature medicine.

[27]  V. Kuznetsov,et al.  Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures , 2014, Cell cycle.

[28]  Enrica Calura,et al.  Association between miR-200c and the survival of patients with stage I epithelial ovarian cancer: a retrospective study of two independent tumour tissue collections. , 2011, The Lancet. Oncology.

[29]  C. Burge,et al.  Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets , 2005, Cell.

[30]  J. Mattick,et al.  Long non-coding RNAs: insights into functions , 2009, Nature Reviews Genetics.

[31]  Xiaoqin Zhang,et al.  A long non-coding RNA signature in glioblastoma multiforme predicts survival , 2013, Neurobiology of Disease.

[32]  Tongbin Li,et al.  miRecords: an integrated resource for microRNA–target interactions , 2008, Nucleic Acids Res..

[33]  Benjamin J. Raphael,et al.  Integrated Genomic Analyses of Ovarian Carcinoma , 2011, Nature.

[34]  Yong Fang,et al.  miR-9 regulation of BRCA1 and ovarian cancer sensitivity to cisplatin and PARP inhibition. , 2013, Journal of the National Cancer Institute.

[35]  M. Gorospe,et al.  miR-182-mediated downregulation of BRCA1 impacts DNA repair and sensitivity to PARP inhibitors. , 2011, Molecular cell.

[36]  K. Gunsalus,et al.  Combinatorial microRNA target predictions , 2005, Nature Genetics.

[37]  D. Livingston,et al.  Physiological modulation of endogenous BRCA1 p220 abundance suppresses DNA damage during the cell cycle , 2013, Genes & development.

[38]  Kailai Sun,et al.  MiR‐125b targets BCL3 and suppresses ovarian cancer proliferation , 2011, International journal of cancer.

[39]  R. Zeillinger,et al.  BRCA1 gene promoter methylation status in high-grade serous ovarian cancer patients--a study of the tumour Bank ovarian cancer (TOC) and ovarian cancer diagnosis consortium (OVCAD). , 2014, European journal of cancer.

[40]  B. Davidson,et al.  miRNA profiling along tumour progression in ovarian carcinoma , 2011, Journal of cellular and molecular medicine.

[41]  Yi-Hsuan Chen,et al.  miRNAMap 2.0: genomic maps of microRNAs in metazoan genomes , 2007, Nucleic Acids Res..

[42]  T. Sellers,et al.  Long-term ovarian cancer survival associated with mutation in BRCA1 or BRCA2. , 2013, Journal of the National Cancer Institute.