Background: MicroRNAs have altered expression levels in various diseases and may play an important role in the diagnosis and prognosis of colorectal cancer (CRC). Methods: We systemically reviewed and quantitatively synthesized the scientific evidence pertaining to microRNA-20a (miR-20a) as a CRC biomarker. A keyword and reference search in PubMed yielded 32 studies, in which miR-20a was measured in feces, serum, or tumor tissue. Data were extracted from a total of 5014 cancer cases and 2863 controls. Results: Twenty out of 21 relevant studies found that miR-20a was upregulated in CRC patients compared to controls. Meta-analysis revealed a pooled miR-20a fold change of 2.45 (95% CI: 2.24–2.66) in CRC patients versus controls. To estimate sensitivity and specificity of miR-20a as a diagnostic biomarker of CRC, a pooled area under the receiver operating characteristic curve (AUROC) was calculated (0.70, 95% CI: 0.63–0.78). The prognostic capacity of miR-20a was assessed using hazard ratios (HRs) for the overall survival (OS). The meta-analysis estimated the pooled HR for OS to be 2.02 (95% CI: 0.90–3.14) in CRC patients with high miR-20a expression. Conclusions: miR-20a may be a valid biomarker for CRC detection but may not be a strong predictor of poor prognosis in CRC.

The screening and diagnosis of colorectal cancer (CRC) currently relies heavily on invasive endoscopic techniques as well as imaging and antigen detection tools. More accessible and reliable biomarkers are necessary for early detection in order to expedite treatment and improve patient outcomes. Recent studies have indicated that levels of specific microRNA (miRNA) are altered in CRC; however, measuring miRNA in biological samples has proven difficult, given the complicated and lengthy PCR-based procedures used by most laboratories. In this manuscript, we examine the potential of miRNA as CRC biomarkers, summarize the methods that have commonly been employed to quantify miRNA, and focus on novel strategies that can improve or replace existing technology for feasible implementation in a clinical setting. These include isothermal amplification techniques that can potentially eliminate the need for specialized thermocycling equipment. Additionally, we propose the use of near-infrared (NIR) probes which can minimize autofluorescence and photobleaching and streamline quantification without tedious sample processing. We suggest that novel miRNA quantification tools will be necessary to encourage new discoveries and facilitate their translation to clinical practice.

Standard methods for detecting cancer-associated genes rely on comparison of sample means between cancer patients and healthy controls. While such methods have successfully identified several oncogenes and tumor suppressor genes, they neglect to account for heterogeneity within the cancer population. Genetic mutations, translocations, and amplifications are often inconsistent across tumors, and instead they often affect smaller subsets of patients. This concept gives rise to the idea of bimodally expressed genes, or genes that display two modes of expression within one population. Analysis of bimodal gene expression has been explored via a variety of techniques including test statistics and clustering. In this review, we summarize the methodologies used to quantify bimodal gene expression and address the utility of these genes in patient stratification and specialized therapeutics in breast and lung cancer. Finally we discuss the limitations and future directions for bimodal genes in the era of high-throughput sequencing and personalized medicine.

Background: Inflammation has been associated with higher rates of recurrence and mortality in head and neck cancer (HNC). While the biological mechanisms predisposing patients to heightened inflammatory states remain largely unknown, DNA methylation has been proposed to reflect systemic inflammation. In this analysis, we attempt to identify meaningful epigenetic patterns in HNC survivors by stratifying individuals based on DNA methylation profiles in leukocytes.Results: We used hierarchical clustering to uncover three distinct methylation patterns among HNC survivors. Each group displayed a unique methylation signature in inflammatory pathways including cytokine and B-cell receptor signaling. Additionally, we examined physiological, clinical, and lifestyle parameters related to inflammation, such as circulating carotenoid and cytokine levels, cancer treatment type, and alcohol consumption. Specifically, we identified one group of survivors who had significant differential methylation of transcriptional and translational regulators as well as genes in the T-cell receptor signaling pathway, including hypermethylation of CD40 ligand (CD40LG) and Tec protein tyrosine kinase (TEC) and hypomethylation ofCD8A. This group also displayed high circulating lycopene levels. We identified another group that had distinctive methylation in the toll-like receptor (TLR) signaling pathway, including hypomethylation ofTLR5, a component of the inhibitor of nuclear factor-kappa B kinase complex (CHUK), and two mitogen-activated protein kinases (MAP3K8andMAP2K3). This group also had hypermethylation of mitochondrial ribosomal genes along with higher rates of alcohol consumption.Conclusion: The correlation between lycopene, alcohol consumption, DNA methylation, and inflammation warrants further investigation and may have implications in future recommendations and interventions to impact health outcomes in HNC survivors.