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Objective: Circular RNAs (circRNAs) are a significant class of molecules involved in a wide range of diverse biological functions that are abnormally expressed in many types of diseases. The present study aimed to determine the circRNAs specifically expressed in peripheral blood mononuclear cells (PBMCs) from rheumatoid arthritis (RA) patients to identify their possible molecular mechanisms. Methods: To identify the circRNAs specifically expressed in RA, we started by sequencing the of PBMCs circRNA and microRNAs (miRNAs) from a RA group (n = 3) and a control group (n = 3). We constructed a network of differentially expressed circRNAs and miRNAs. Then, we selected differentially expressed circRNAs in PBMCs from 10 RA patients relative to 10 age-and sex-matched controls using real-time quantitative reverse transcription-polymerase chain reaction (RT-qPCR). Spearman's correlation test was used to evaluate the correlation of circRNAs with biochemical measurements. Results: A total of 165 circRNAs and 63 miRNAs were differently expressed between RA patients and healthy people according to RNA-seq, including 109 circRNAs that were significantly up-regulated and 56 circRNAs that were down-regulated among the RA patients. RT-qPCR validation demonstrated that the expression levels of hsa circ 0001200, hsa circ 0001566, hsa circ 0003972, and hsa circ 0008360 were consistent with the results from the sequencing analysis. Then, we found that there were significant correlations between the circRNAs and disease severity. Conclusion: Generally, these results suggest that expression of hsa circ 0001200, hsa circ 0001566, hsa circ 0003972, and hsa circ 0008360 in PBMCs from RA patients may serve as potential biomarkers for the diagnosis of RA, and these circRNAs may influence the occurrence and development of RA.

The AJCC Cancer Staging Manual, eighth edition published in late 2016, will become the new global guideline for cancer diagnosis and treatment from January 1, 2018. The new edition for the tumor staging system has numerous updates, including building up the prognostic stage group of tumors for the first time and adding a large number of non-anatomical factors into the prognostic evaluation. Oncotype DX and MammaPrint are two of the genomic predictors that will be part of routine clinical practice in the future. Numerous studies have proved the clinical utility of multigene panels in predicting clinical outcome and treatment response. Here we present our review of the studies on these multigene panels and their application to breast cancer.

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