Innate and acquired chemoresistance exhibited by most tumours exposed to conventional chemotherapeutic agents account for the majority of relapse cases in cancer patients. Such chemoresistance phenotypes are of a multi-factorial nature from multiple key molecular players. The discovery of the RNA interference pathway in 1998 and the widespread gene regulatory influences exerted by microRNAs (miRNAs) and other non-coding RNAs have certainly expanded the level of intricacy present for the development of any single physiological phenotype, including cancer chemoresistance. This review article focuses on the latest research efforts in identifying and validating specific key molecular players from the two main families of non-coding RNAs, namely miRNAs and long non-coding RNAs (lncRNAs), having direct or indirect influences in the development of cancer drug resistance properties and how such knowledge can be utilised for novel theranostics in oncology.

Long non-coding RNAs (lncRNAs), a class of non-coding transcripts, have recently been emerging with heterogeneous molecular actions, adding a new layer of complexity to generegulation networks in tumorigenesis. LncRNAs are considered important factors in several ovarian cancer histotypes, although few have been identified and characterized. Owing to their complexity and the lack of adapted molecular technology, the roles of most lncRNAs remain mysterious. Some lncRNAs have been reported to play functional roles in ovarian cancer and can be used as classifiers for personalized medicine. The intrinsic features of lncRNAs govern their various molecular mechanisms and provide a wide range of platforms to design different therapeutic strategies for treating cancer at a particular stage. Although we are only beginning to understand the functions of lncRNAs and their interactions with microRNAs (miRNAs) and proteins, the expanding literature indicates that lncRNA-miRNA interactions could be useful biomarkers and therapeutic targets for ovarian cancer. In this review, we discuss the genetic variants of lncRNAs, heterogeneous mechanisms of actions of lncRNAs in ovarian cancer tumorigenesis, and drug resistance. We also highlight the recent developments in using lncRNAs as potential prognostic and diagnostic biomarkers. Lastly, we discuss potential approaches for linking lncRNAs to future gene therapies, and highlight future directions in the field of ovarian cancer research.

BackgroundThe quantification of gene expression in tissue samples requires the use of reference genes to normalise transcript numbers between different samples. Reference gene stability may vary between different tissues, and between the same tissue in different disease states. We evaluated the stability of 9 reference genes commonly used in human gene expression studies. Real-time reverse transcription PCR and a mathematical algorithm were used to establish which reference genes were most stably expressed in normal and diseased canine articular tissues and two canine cell lines stimulated with lipolysaccaride (LPS).ResultsThe optimal reference genes for comparing gene expression data between normal and diseased infrapatella fat pad were RPL13A and YWHAZ (M = 0.56). The ideal reference genes for comparing normal and osteoarthritic (OA) cartilage were RPL13A and SDHA (M = 0.57). The best reference genes for comparing normal and ruptured canine cranial cruciate ligament were B2M and TBP (M = 0.59). The best reference genes for normalising gene expression data from normal and LPS stimulated cell lines were SDHA and YWHAZ (K6) or SDHA and HMBS (DH82), which had expression stability (M) values of 0.05 (K6) and 0.07 (DH82) respectively. The number of reference genes required to reduce pairwise variation (V) to <0.20 was 4 for cell lines, 5 for cartilage, 7 for cranial cruciate ligament and 8 for fat tissue. Reference gene stability was not related to the level of gene expression.ConclusionThe reference genes demonstrating the most stable expression within each different canine articular tissue were identified, but no single reference gene was identified as having stable expression in all different tissue types. This study underlines the necessity to select reference genes on the basis of tissue and disease specific expression profile evaluation and highlights the requirement for the identification of new reference genes with greater expression stability for use in canine articular tissue gene expression studies.