Biomarker potential of repetitive-element transcriptome in lung cancer.

Since repetitive elements (REs) account for nearly 53% of the human genome, profiling its transcription after an oncogenic change might help in the search for new biomarkers. Lung cancer was selected as target since it is the most frequent cause of cancer death. A bioinformatic workflow based on well-established bioinformatic tools (such as RepEnrich, RepBase, SAMTools, edgeR and DESeq2) has been developed to identify differentially expressed RNAs from REs. It was trained and tested with public RNA-seq data from matched sequencing of tumour and healthy lung tissues from the same patient to reveal differential expression within the RE transcriptome. Healthy lung tissues express a specific set of REs whose expression, after an oncogenic process, is strictly and specifically changed. Discrete sets of differentially expressed REs were found for lung adenocarcinoma, for small-cell lung cancer, and for both cancers. Differential expression affects more HERV-than LINE-derived REs and seems biased towards down-regulation in cancer cells. REs behaving consistently in all patients were tested in a different patient cohort to validate the proposed biomarkers. Down-regulation of AluYg6 and LTR18B was confirmed as potential lung cancer biomarkers, while up-regulation of HERVK11D-Int is specific for lung adenocarcinoma and up-regulation of UCON88 is specific for small cell lung cancer. Hence, the study of RE transcriptome might be considered another research target in cancer, making REs a promising source of lung cancer biomarkers.

Automated identification of reference genes based on RNA-seq data.

BACKGROUND: Gene expression analyses demand appropriate reference genes (RGs) for normalization, in order to obtain reliable assessments. Ideally, RG expression levels should remain constant in all cells, tissues or experimental conditions under study. Housekeeping genes traditionally fulfilled this requirement, but they have been reported to be less invariant than expected; therefore, RGs should be tested and validated for every particular situation. Microarray data have been used to propose new RGs, but only a limited set of model species and conditions are available; on the contrary, RNA-seq experiments are more and more frequent and constitute a new source of candidate RGs. RESULTS: An automated workflow based on mapped NGS reads has been constructed to obtain highly and invariantly expressed RGs based on a normalized expression in reads per mapped million and the coefficient of variation. This workflow has been tested with Roche/454 reads from reproductive tissues of olive tree (Olea europaea L.), as well as with Illumina paired-end reads from two different accessions of Arabidopsis thaliana and three different human cancers (prostate, small-cell cancer lung and lung adenocarcinoma). Candidate RGs have been proposed for each species and many of them have been previously reported as RGs in literature. Experimental validation of significant RGs in olive tree is provided to support the algorithm. CONCLUSION: Regardless sequencing technology, number of replicates, and library sizes, when RNA-seq experiments are designed and performed, the same datasets can be analyzed with our workflow to extract suitable RGs for subsequent PCR validation. Moreover, different subset of experimental conditions can provide different suitable RGs.

Spotlight on ramucirumab in the treatment of nonsmall cell lung cancer: design, development, and clinical activity.

The vascular endothelial growth factor (VEGF) and receptor is a therapeutic target because of the importance of this pathway in carcinogenesis. This pathway regulates and promotes angiogenesis as well as increases endothelial cell proliferation, permeability, and cancer survival. Ramucirumab is a new fully human monoclonal antibody that targets the VEGF receptor-2, an important key receptor implicated in angiogenesis. Ramucirumab has been approved for the treatment of second-line advanced or metastatic non-small cell lung cancer (NSCLC) in combination with the chemotherapy agent docetaxel. This was based on the result of the randomized trial REVEL of 1,253 patients with metastatic NSCLC previously treated with a platinum-based combination therapy. The authors observed a significant improvement in overall survival (OS) with an acceptable toxicities profile. In this study, patients were randomized to receive ramucirumab plus docetaxel or placebo with docetaxel. The combination of docetaxel and ramucirumab showed an improved OS (hazard ratio [HR]: 0.86; 95% CI: 0.75, 0.98). Median OS was 10.5 months in the ramucirumab arm versus 9.1 months in the placebo arm. Regarding side effects, the toxicity described on the ramucirumab arm were principally diarrhea, fatigue, and neutropenia. The most common (5%) adverse reactions of grade 3 and 4 in the ramucirumab arm were fatigue, neutropenia, febrile neutropenia, leukopenia, and hypertension. Adding ramucirumab to docetaxel improves QoL of patients, and does not impair symptoms or functioning. There are currently several trials in progress evaluating the effects of ramucirumab in combination with other drugs in patients with advanced NSCLC.