RNA biomarkers in colorectal cancer

Colorectal cancer (CRC) develops and progresses through a systematic selection for (epi) genetic alterations that drive the transformation from normal colon epithelium to adenocarcinoma. These changes affect both noncoding RNAs and mRNAs and so define the clinical behaviour of cancer cells within a distinctive host genetic and environmental context. Although earlier diagnosis and more effective treatment modalities have decreased mortality from CRC, prognostic stratification and adjuvant therapy selection after surgery remain dependent on broad descriptive classifications, opportune histological markers of poor prognosis and chemotherapy efficacy data derived from diverse CRC populations. Crucially, there is significant inter- and intra-individual variability in response to, and tolerance of, chemotherapy treatments. These limitations explain the small clinical benefit of new agents studied in contemporary phase III trials. Molecular assays have the potential to address these constraints and there has been intense interest in the identification of clinically relevant molecular biomarkers. These must be easy to obtain and quantify and ideally represent steps in well-understood carcinogenic pathways or host-response mechanisms. Although some biomarkers can provide broad prognostic information based on CRC subtype (e.g. MSI status) or can somewhat predict response to targeted therapies (e.g. KRAS), no RNA-based biomarkers have entered routine clinical practice. This is due, in part, to the genetic heterogeneity of both patients and CRC. In addition, serious underlying issues with regards to study design, poor technical protocols, inadequate quality controls and inappropriate data analysis prevent successful translation of research results. Consequently, the identification of clinically relevant panels of biomarkers will depend not just on further advances in our understanding of CRC biology, but will need to be coupled with appropriate study designs and more suitable, standardised and transparent techniques

Metasin — An Intra-Operative RT-qPCR Assay to Detect Metastatic Breast Cancer in Sentinel Lymph Nodes

Nodal status is one of the most important prognostic factors in breast cancer. Established tests such as touch imprint cytology and frozen sections currently used in the intra-operative setting show variations in sensitivity and specificity. This limitation has led to the development of molecular alternatives, such as GeneSearch, a commercial intra-operative real-time quantitative Polymerase Chain Reaction (RT-qPCR) assay that allows the surgeon to carry out axillary clearance as a one-step process. Since GeneSearch has been discontinued, we have developed the replacement Metasin assay, which targets the breast epithelial cell markers CK19 and mammaglobin mRNA and identifies metastatic disease in sentinel lymph nodes. The optimised assay can be completed within 32 min (6 min for RNA preparation and 26 min instrument run time), making its use feasible in the intraoperative setting. An analysis by Metasin of 154 archived lymph node homogenates previously analysed by both parallel histology and GeneSearch showed concordance for 148 cases. The sensitivity and specificity of Metasin compared with GeneSearch were 95% (CI 83%-99%) and 97% (CI 91%-99%) respectively; compared with histology they were 95% (CI 83%-99%) and 97% (CI 91%-99%), respectively. The sensitivity and specificity of GeneSearch compared with histology were 90% (CI 77%-96%) and 97% (CI 93%-99%) respectively. The positive predictive value of Metasin was 90% and negative predictive value was 98% for both histology and GeneSearch. The positive predictive value of GeneSearch was 92% and the negative predictive value was 97% compared to histology. The discordance rates of Metasin with both GeneSearch and histology were 3.89%. In comparison, the discordance rate of GeneSearch with histology was 4.5%. Metasin's robustness was independently evaluated on 193 samples previously analysed by GeneSearch from the Jules Bordet Institute, where Metasin yielded comparable results

Strand-specific miR-28-5p and miR-28-3p have distinct effects in colorectal cancer cells

The authors thank Sue Moreau from the Department of Scientific Publications at The University of Texas MD Anderson Cancer Center for English language editing of the manuscript. Author contributions: Study concept and design: M.I.A., P.A.Z, G.A.C. Acquisition of data: M.I.A., L.Z., X.Z. Drafting of the manuscript: M.I.A., M.N., R.S., M.F., R.M.R., P.A.Z, G.A.C. Analysis and interpretation of data: M.I.A., M.N., R.S., R.M., P.A.Z, G.A.C. Critical revision of the manuscript for important intellectual content: M.I.A., M.N., R.S., M.F., R.M.R., P.A.Z, G.A.C. Statistical analysis: M.I.A., C.I., L.X. Obtained funding: G.A.C. Administrative, technical, or material support: R.G., I.V., F.F., M.F., G.L. Study supervision: G.A.C. Drs Nicoloso and Spizzo are currently at the Division of Experimental Oncology, CRO, National Cancer Institute, Aviano, ItalyBackground & Aims MicroRNAs (miRNAs) can promote or inhibit tumor growth and are therefore being developed as targets for cancer therapies. They are diverse not only in the messenger RNAs (mRNA) they target, but in their production; the same hairpin RNA structure can generate mature products from each strand, termed 5p and 3p, that can bind different mRNAs. We analyzed the expression, functions, and mechanisms of miR-28-5p and miR-28-3p in colorectal cancer (CRC) cells. Methods We measured levels of miR-28-5p and miR-28-3p expression in 108 CRC and 49 normal colorectal samples (47 paired) by reverse transcription, quantitative real-time polymerase chain reaction. The roles of miR-28 in CRC development were studied using cultured HCT116, RKO, and SW480 cells and tumor xenograft analyses in immunodeficient mice; their mRNA targets were also investigated. Results miR-28-5p and miR-28-3p were down-regulated in CRC samples compared with normal colon samples. Overexpression of miRNAs in CRC cells had different effects and the miRNAs interacted with different mRNAs: miR-28-5p altered expression of CCND1 and HOXB3, whereas miR-28-3p bound NM23-H1. Overexpression of miR-28-5p reduced CRC cell proliferation, migration, and invasion in vitro, whereas miR-28-3p increased CRC cell migration and invasion in vitro. CRC cells overexpressing miR-28 developed tumors more slowly in mice compared with control cells, but miR-28 promoted tumor metastasis in mice. Conclusion miR-28-5p and miR-28-3p are transcribed from the same RNA hairpin and are down-regulated in CRC cells. Overexpression of each has different effects on CRC cell proliferation and migration. Such information has a direct application for the design of miRNA gene therapy trials.M.I.A. is supported by a PhD fellowship (SFRH/BD/47031/2008) from Fundação para a Ciência e Tecnologia, Portugal. G.A.C. is supported as a fellow by The University of Texas MD Anderson Cancer Center Research Trust, The University of Texas System Regents Research Scholar, and the Chronic Lymphocytic Leukemia Global Research Foundation. Work in Dr Calin’s laboratory is supported in part by grants from the National Institutes of Health (CA135444), the US Department of Defense, the Pancreatic Cancer Action Network (2009 Seena Magowitz AACR Pilot Grant), and the US-European Alliance for the Therapy of Chronic Lymphoid Leukemia. STR DNA fingerprinting was done by the Cancer Center Support grant funded Characterized Cell Line core, NCI # CA16672

A multicentre validation of Metasin: a molecular assay for the intraoperative assessment of sentinel lymph nodes from breast cancer patients

Aims: Treatment strategies for breast cancer continue to evolve. No uniformity exists in the UK for the management of node‐positive breast cancer patients. Most centres continue to use conventional histopathology of sampled sentinel lymph nodes (SLNs), which requires delayed axillary clearance in up to 25% of patients. Some use touch imprint cytology or frozen section for intraoperative testing, although both have inherent sensitivity issues. An intraoperative molecular diagnostic approach helps to overcome some of these limitations. The aim of this study was to assess the clinical effectiveness of Metasin, a molecular method for the intraoperative evaluation of SLNs. Methods and results: RNA from 3296 lymph nodes from 1836 patients undergoing SLN assessment was analysed with Metasin. Alternate slices of tissue were examined in parallel by histology. Cases deemed to be discordant were analysed by protein gel electrophoresis. There was concordance between Metasin and histology in 94.1% of cases, with a sensitivity of 92% [95% confidence interval (CI) 88–94%] and a specificity of 97% (95% CI 95–97%). Positive and negative predictive values were 88% and 98%, respectively. Over half of the discordant cases (4.4%) were ascribed to tissue allocation bias (TAB). Conclusions: Clinical validation of the Metasin assay suggests that it is sufficiently sensitive and specific to make it fit for purpose in the intraoperative setting

Genetic data: The new challenge of personalized medicine, insights for rheumatoid arthritis patients

Rapid advances in genotyping technology, analytical methods, and the establishment of large cohorts for population genetic studies have resulted in a large new body of information about the genetic basis of human rheumatoid arthritis (RA). Improved understanding of the root pathogenesis of the disease holds the promise of improved diagnostic and prognostic tools based upon this information. In this review, we summarize the nature of new genetic findings in human RA, including susceptibility loci and gene-gene and gene-environment interactions, as well as genetic loci associated with sub-groups of patients and those associated with response to therapy. Possible uses of these data are discussed, such as prediction of disease risk as well as personalized therapy and prediction of therapeutic response and risk of adverse events. While these applications are largely not refined to the point of clinical utility in RA, it seems likely that multi-parameter datasets including genetic, clinical, and biomarker data will be employed in the future care of RA patients