Nanoplasmonic sensors for detecting circulating cancer biomarkers

The detection of cancer biomarkers represents an important aspect of cancer diagnosis and prognosis. Recently, the concept of liquid biopsy has been introduced whereby diagnosis and prognosis are performed by means of analyzing biological fluids obtained from patients to detect and quantify circulating cancer biomarkers. Unlike conventional biopsy whereby primary tumor cells are analyzed, liquid biopsy enables the detection of a wide variety of circulating cancer biomarkers, including microRNA (miRNA), circulating tumor DNA (ctDNA), proteins, exosomes and circulating tumor cells (CTCs). Among the various techniques that have been developed to detect circulating cancer biomarkers, nanoplasmonic sensors represent a promising measurement approach due to high sensitivity and specificity as well as ease of instrumentation and operation. In this review, we discuss the relevance and applicability of three different categories of nanoplasmonic sensing techniques, namely surface plasmon resonance (SPR), localized surface plasmon resonance (LSPR) and surface-enhanced Raman scattering (SERS), for the detection of different classes of circulating cancer biomarkers.

Non-coding RNAs Enabling Prognostic Stratification and Prediction of Therapeutic Response in Colorectal Cancer Patients

Colorectal cancer (CRC) is a heterogeneous disease and current treatment options for patients are associated with a wide range of outcomes and tumor responses. Although the traditional TNM staging system continues to serve as a crucial tool for estimating CRC prognosis and for stratification of treatment choices and long-term survival, it remains limited as it relies on macroscopic features and cases of surgical resection, fails to incorporate new molecular data and information, and cannot perfectly predict the variety of outcomes and responses to treatment associated with tumors of the same stage. Although additional histopathologic features have recently been applied in order to better classify individual tumors, the future might incorporate the use of novel molecular and genetic markers in order to maximize therapeutic outcome and to provide accurate prognosis. Such novel biomarkers, in addition to individual patient tumor phenotyping and other validated genetic markers, could facilitate the prediction of risk of progression in CRC patients and help assess overall survival. Recent findings point to the emerging role of non-protein-coding regions of the genome in their contribution to the progression of cancer and tumor formation. Two major subclasses of non-coding RNAs (ncRNAs), microRNAs and long non-coding RNAs, are often dysregulated in CRC and have demonstrated their diagnostic and prognostic potential as biomarkers. These ncRNAs are promising molecular classifiers and could assist in the stratification of patients into appropriate risk groups to guide therapeutic decisions and their expression patterns could help determine prognosis and predict therapeutic options in CRC.

microRNAs in cancer management

Since the identification of microRNAs (miRNAs) in 1993, and the subsequent discovery of their highly conserved nature in 2000, the amount of research into their function--particularly how they contribute to malignancy--has greatly increased. This class of small RNA molecules control gene expression and provide a previously unknown control mechanism for protein synthesis. As such, it is unsurprising that miRNAs are now known to play an essential part in malignancy, functioning as tumour suppressors and oncogenes. This Review summarises the present understanding of how miRNAs operate at the molecular level; how their dysregulation is a crucial part of tumour formation, maintenance, and metastasis; how they can be used as biomarkers for disease type and grade; and how miRNA-based treatments could be used for diverse types of malignancies.

Systematic analysis of regulation and functions of co-expressed microRNAs in humans

MicroRNAs (miRNAs) are a class of small non-coding RNA genes that post-transcriptionally regulate gene expression. With the development of high-throughput miRNA detection technology, researchers have begun to investigate the relationships between miRNA expression and its functions. In this study, we systematically analyzed the underlying molecular mechanisms and biological functions of co-expressed miRNAs. By integrating miRNA expression profiles, miRNA genome locations, transcriptional factors (TFs) of miRNAs and their target genes, we concluded that co-expressed miRNAs are more likely to be located in the same miRNA cluster (p = 6.05 x 10(-30)), are regulated by more common TFs (p = 9.17 x 10(-17)) and have consistent functions (p = 1.01 x 10(-6)). Moreover, among the top 10% (84) co-expressed miRNA pairs that are located on the same chromosomes, 37 miRNA pairs are located in the same cluster. Of the remaining 47 pairs, 36 miRNA pairs share more common TFs (>7). They account for 73/84 (86.9%) of total miRNA pairs. Finally, we further analyzed the top 10 co-expressed miRNA pairs. Almost all of these miRNA pairs are located in the same cluster, are regulated by many common TFs and have highly consistent functions, in agreement with previous reports. Thus, our study may provide an important reference for miRNA regulations and functions.