Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cause of cancer mortality in the world. Some progress has been made in the therapy of HNSCC, however treatment remains unsatisfactory. Recent studies have shown that different types of long non-coding RNAs (lncRNAs) are dysregulated in HNSCC and correlate with tumor progression, lymph node metastasis, clinical stage and poor prognosis. lncRNAs are a class of functional RNA molecules that can not be translated into proteins but can modulate the activity of transcription factors or regulate changes in chromatin structure. The lncRNAs might have potential of biomarker in HNSCC diagnosis, prognosis, prediction and targeted treatment. In this review we describe the potential role of lncRNAs as new biomarkers and discuss their features including source of origin, extraction methods, stability, detection methods and data normalization and potential function as biomarkers in HNSCC.

Head and neck squamous cell carcinoma (HNSCC) are one of the worst prognosis cancers with high mortality of patients. The treatment strategy is primarily based on surgery and radiotherapy but chemotherapy is also used. Every year the knowledge concerning HNSCC biology is updated with new elements such as the recent discovered molecules - long non-coding RNAs. Long non-coding RNAs are involved in regulatory processes in the cells. It has been revealed that the expression levels of lncRNAs are disturbed in tumor cells what results in the acquisition of their specific phenotype. lncRNAs influence cell growth, cell cycle, cell phenotype, migration and invasion ability as well as apoptosis. Development of the lncRNA panel characteristic for HNSCC and validation of specific lncRNA functions are yet to be elucidated. In this work, we collected available data concerning lncRNAs in HNSCC and characterized their biological role. We believe that the tumor examination, in the context of lncRNA expression, may lead to understanding complex biology of the cancer and improve therapeutic methods in the future.

Long non-coding RNAs (lncRNA) are dysregulated in many cancer types. Abnormal baseline levels of these lncRNAs display diagnostic and prognostic potential in cancer patients. The aim of this study was to evaluate the prognostic value of plasma lncRNAs in BRAF -mutant advanced melanoma patients treated with a BRAF inhibitor. Total RNA was isolated from plasma samples collected from 58 advanced BRAF-mutant melanoma patients and 15 healthy donors. The expression levels of 90 lncRNAs were estimated using the LncProfiler qPCR Array Kit (SBI) and LightCycler 96 (Roche). LncRNA expression levels correlated with responses to the BRAF inhibitor (vemurafenib) treatment. The patients were stratified into three groups based on their lncRNA levels with various lncRNA expressions (low, medium, and high). A Cox proportional hazards regression model was used to determine the lncRNAs that were significantly associated with both progression-free and overall survivals (PFS and OS, respectively) in patients receiving vemurafenib. The expression level of 12 lncRNAs was down-regulated, while five lncRNAs were up-regulated in melanoma patients compared to healthy donors. Kaplan-Meier analysis showed that upregulation or downregulation of 11 and 16 different lncRNAs were associated with longer median PFS and OS, respectively. Further analysis demonstrated that the baseline lncRNAs for IGF2AS, anti-Peg11, MEG3, Zeb2NAT are independent prognostic factors in BRAF -mutant advanced melanoma patients treated with vemurafenib. Evaluation of plasma lncRNAs expression level for advanced melanoma diagnosis and prognosis evaluation appears to be a safe and valuable method; however, this method requires further validation in larger cohorts and randomized trials.

Introduction: Long non-coding RNAs (lncRNAs), a class of regulatory RNA molecules, are over 200 nucleotides long and could be used as a new potential biomarker, but their detection methods such as qRT-PCR are still not validated, and the influence of RNA degradation on lncRNA quantification is not clear. In this study, commercially available cDNA synthesis kits were tested and the influence of RNA degradation was compared. Material and methods: Total RNA from FaDu cells was isolated and high quality RNA and highly degraded RNA samples were used. Reverse transcription was performed using three different commercially available kits and quantifications were performed using lncRNA Primer Plate and SYBR Green I Master by LightCycler 96. qRT-PCR was performed using three different cDNA samples and results are presented as the mean Ct values. A p-value < 0.05 was considered to be significant. Results: Lower lncRNA Ct values (61/90; 67.78%) after qRT-PCR quantification were observed for cDNA synthesized using random hexamer primers preceded by polyA-tailing and adaptor-anchoring steps. It was observed that 9/90 (10.00%) lncRNAs were not detectable using different cDNA synthesis methods. For 75/90 (83%) lncRNAs, RNA degradation weakly influenced lncRNA Ct values and no differences were observed between high quality RNA and degraded samples. Seventy percent of examined lncRNAs showed significantly different Ct values depending on RNA degradation. Conclusions: cDNA synthesis kits with random hexamer primers preceded by polyA-tailing and adaptor-anchoring steps allows enhancement of lncRNA quantification specificity and sensitivity. In most cases degradation of RNA samples does not affect lncRNA quantification because these molecules have good stability.