Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a Systems Biology Approach.

Cutaneous melanoma is the most aggressive type of skin cancer which its incidence has significantly increased in recent years worldwide. Thus, more investigations are required to identify the underlying mechanisms of melanoma malignant transformation and metastasis. In this context, long noncoding RNAs (lncRNAs) are a new type of noncoding transcripts that their dysregulations are associated with almost all cancers including melanoma. However, the precise functional roles of most of the significantly altered lncRNAs in melanoma have not yet been fully inspected. In this study, a comprehensive list of lncRNAs was interrogated across cutaneous melanoma samples to identify the significantly altered/dysregulated lncRNAs. To this end, lncRNAs were filtered in several steps and the selected lncRNAs projected to a bioinformatic and systems biology analysis using several publicly available databases and tools such as GEPIA and cBioPortal. According to our results, 30 lncRNAs were notably altered/dysregulated in cutaneous melanoma most of which were co-expressed with each other. Also, co-expression/alteration and differential expression analyses led to the selection of 12 out of these 30 lncRNAs as cutaneous melanoma key lncRNAs. Furthermore, functional demonstrated that these 12 lncRNAs might be involved in melanoma-relevant biological processes and pathways. In addition, the end result of our analyses demonstrated that these lncRNAs are associated with the clinicopathological features of melanoma patients. These 12 lncRNAs need to be further investigated in future studies to characterize their exact roles in melanoma development and to identify their potential for being used as drug targets and/or biomarkers for cutaneous melanoma.

Potential role of RAB6C-AS1 long noncoding RNA in different cancers.

BACKGROUND: Long noncoding RNAs (lncRNAs) refer to a group of non-protein-coding RNAs that are usually more than 200 nucleotides. These long transcripts play significant roles in diverse cellular processes, mostly through epigenetic mechanisms. Thus, dysregulation of lncRNAs is associated with various diseases, especially cancer. This study aims to investigate the probable roles of RAB6C-AS1 lncRNA in different cancers. METHODS: Real-time quantitative reverse transcription-polymerase chain reaction was applied for the analysis of RAB6C-AS1 lncRNA amplification in gastric cancer (GC) samples compared with normal ones. Also, several online and offline data sets and tools were used to analyze the relation between RAB6C-AS1 lncRNA and different cancers. RESULTS: The end result of our analyses indicated that RAB6C-AS1 was overexpressed in 40% of the investigated GC specimens. Also, the results demonstrated a true relation between RAB6C-AS1 overexpression and higher GC tumor grades. However, bioinformatic analyses showed that while RAB6C-AS1 possibly functions as an oncogene in some cancer types, including prostate and breast cancers, it might have a tumor suppressive function in some others including brain tumors. CONCLUSIONS: We found that RAB6C-AS1 lncRNA is mostly overexpressed in GC. Also, based on bioinformatic and systems biology analyses, RAB6C-AS1 might function either as an oncogenic factor or tumor suppressor in a tissue-specific manner. Thus, RAB6C-AS1 could be considered as a candidate biomarker for various malignancies, especially prostate and brain cancers. According to our results, RAB6C-AS1 has a notable prognostic value for patients with brain lower grade glioma.

Bioinformatic Analysis of Circadian Expression of Oncogenes and Tumor Suppressor Genes.

BACKGROUND: Circadian rhythms are physiological and behavioral cycles with a period of approximately 24 hours that control various functions including gene expression. Circadian disruption is associated with a variety of diseases, especially cancer. Although some of the oncogenes and tumor suppressor genes (TSGs) are known as clock-controlled genes (CCGs), the analysis and annotation of circadian expression of most human oncogenes and TSGs are still lacking. This study aims to investigate the circadian expression of a list of human oncogenes and TSGs. METHODS: A bioinformatic analysis was conducted on a gene library comprising 120 genes to investigate the circadian expression of human oncogenes and TSGs. To achieve this purpose, the genotranscriptomic data were retrieved from COSMIC and analyzed by R statistical software. Furthermore, the acquired data were analyzed at the transcriptomic and proteomic levels using several publicly available databases. Also, the significance of all analyses was confirmed statistically. RESULTS: Altogether, our results indicated that 7 human oncogenes/TSGs may be expressed and function in a circadian manner. These oncogenes/TSGs showed a circadian expression pattern at CircaDB database and associated with at least one of the circadian genes/CCGs based on both genotranscriptomic and correlation analyses. CONCLUSIONS: Although 4 of 7 finally outputted genes have been previously reported to be clock controlled, heretofore there is no report about the circadian expression of 3 other genes. Considering the importance of oncogenes/TSGs in the initiation and progression of cancer, further studies are suggested for the identification of exact circadian expression patterns of these 3 human oncogenes/TSGs.