Assessing the potential relevance of CEACAM6 as a blood transcriptional biomarker

Abstract

Background Changes in blood transcript abundance levels have been associated with pathogenesis in a wide range of diseases. While next generation sequencing technology can measure transcript abundance on a genome-wide scale, downstream clinical applications often require small sets of genes to be selected for inclusion in targeted panels. Here we set out to gather information from the literature and transcriptome datasets that would help researchers determine whether to include the gene CEACAM6 in such panels. Methods We employed a workflow to systematically retrieve, structure, and aggregate information derived from both the literature and public transcriptome datasets. It consisted of profiling the CEACAM6 literature to identify major diseases associated with this candidate gene and establish its relevance as a biomarker. Accessing blood transcriptome datasets identified additional instances where CEACAM6 transcript levels differ in cases vs controls. Finally, the information retrieved throughout this process was captured in a structured format and aggregated in interactive circle packing plots. Results Although it is not routinely used clinically, the relevance of CEACAM6 as a biomarker has already been well established in the cancer field, where it has invariably been found to be associated with poor prognosis. Focusing on the blood transcriptome literature, we found studies reporting elevated levels of CEACAM6 abundance across a wide range of pathologies, especially diseases where inflammation plays a dominant role, such as asthma, psoriasis, or Parkinson’s disease. The screening of public blood transcriptome datasets completed this picture, showing higher abundance levels in patients with infectious diseases caused by viral and bacterial pathogens. Conclusions Targeted assays measuring CEACAM6 transcript abundance in blood may be of potential utility for the management of patients with diseases presenting with systemic inflammation and for the management of patients with cancer, where the assay could potentially be run both on blood and tumor tissues.