Search

Lung cancer (LC) is the most common cause of cancer death worldwide mostly due to the low survival rate: 75% of cases are identified in advanced stages. In this study, the list of useful biomarkers to make an early diagnosis using liquid biopsies was expanded. A total of 30 samples of LC were analyzed to define potential miRNA biomarkers in liquid biopsies for LC. The biomarkers have been identified in interaction networks miRNA–mRNA. The potential biomarkers have been then validated in large cohorts. A total of 15 candidate miRNAs, that regulate the repression of 30 mRNAs, have been identified as a specific functional interaction network for squamous carcinoma, while the specific functional interaction network of adenocarcinoma consists of four candidate miRNAs that seem to handle the repression of five mRNA. Inspection of expression levels in larger cohorts validates the usefulness of the 11 candidates as biomarkers in liquid biopsies. The 11 candidate miRNAs found could be utilized to form diagnostic predictive biomarkers for LC in liquid biopsies.

Lung cancer is one of the deadliest cancers in the world. Its histological classification depends on early diagnosis and successful treatment. Therefore, having specific biomarkers for a quick sorting widens the successful output of lung cancer treatment. High-throughput sequencing (RNA-seq) was performed of small cohorts of BioBanco samples from healthy and tumour cells from lung adenocarcinoma (LUAD) and squamous cell carcinoma of the lung (lSCC). RNA-seq samples from small cell lung cancer (SCLC) were downloaded from databases. A bioinformatic workflow has been programmed for the identification of differentially expressed genes (DEGs). A total of 4777 DEGs were differentially expressed in SCLC, 3676 DEGs were in lSCC, while the lowest number of DEGs, 2819, appeared in LUAD. Among them, 945 DEGs were common to the three histological types. Once validated their expression profile and their survival predictive capacity in large, public cohorts, three DEGs can be exclusively considered as diagnostic biomarkers, three as prognosis biomarkers, and other three exhibit both diagnosis and prognosis capabilities. This prospective study presents evidences for the diagnostic and prognostic capabilities of expression changes in CAPN8-2, TMC5 and MUC1 in LUAD, while they are non-significant in SCLC and lSCC. Their translation to clinical practice is proposed.

RNA-based high-throughput sequencing technologies provide a huge amount of reads from transcripts. In addition to expression analyses, transcriptome reconstruction, or isoform detection, they could be useful for detection of gene variations, in particular micro-variations (single nucleotide polymorphisms [SNPs] and indels). Gene variations are usually based on homogenous (one single individual) DNA-seq data, but this study aims the usage of heterogeneous (several individuals) RNA-seq data to obtain clues about gene variability of a population. Therefore, new algorithms or workflows are required to fill this gap, usually disregarded. Here it is presented an automated workflow based on existing software to predict micro-variations from RNA-seq data using a genome or a transcriptome as reference. It can deal with organism whose genome sequence is known and well-annotated, as well as non-model organism where only draft genomes or transcriptomes are available. Mapping is based on STAR in both cases. Micro-variation detection relies on GATK (combining Mutect2 and HaplotypeCaller) and VarScan since they are able to provide reliable results from RNA-seq reads. The workflow has been tested with reads from normal and diseased lung from patients having small-cell lung carcinoma. Human genome, as well as human transcriptome, were used as reference and then compared: from the initial 120 000 micro-variations, only 267 were predicted by at least two algorithm in the exome of patients. The workflow was tested in non-model organisms such as Senegalese sole, using its transcriptome as reference, to determine micro-variations in sole larvae exposed to different salinities. Therefore, the workflow seems to produce robust and reliable micro-variations in coding genes based on RNA-seq, irrespective of the nature of the reference sequence. We think that this paves the way to correlate micro-variations and differentially expressed genes in non-model organisms with the aim of foster breeding plans.

Recent studies using high-throughput sequencing technologies have demonstrated that transposable elements seem to be involved not only in some cancer onset but also in cancer development. However, their activity is not easy to assess due to the large number of copies present throughout the genome. In this study NearTrans bioinformatic workflow has been used with RNA-seq data from 16 local patients with lung cancer, 8 with adenocarcinoma and 8 with small cell lung cancer. We have found 16 TE-gene pairs significantly expressed in the first disease, and 32 TE-gene pairs the second. Interestingly, some of the genes have been previously described as oncogenes, indicating that normal lung cell compromised on an oncogenic change displays some transposon expression reprogramming that seems to be genome-location dependent. Supporting this is the finding that most differentially expressed transposons change their expression in the same direction than their adjacent genes, and with a similar level of change. The analysis of adjacent genes may reveal or confirm important lung cancer biomarkers as well as new insights in its molecular basis.

Introduction: Since the most common lung cancers are lung adenocarcinoma, squamous lung cancer (SLC) and the small cell lung cancer (SCLC), a comparative diferential expression between these types of lung cancer deserves investigation. Material and Methods: RNA-seq data were obtained for samples from tumoral and adjacent healthy tissue from adenocarcinoma (7 patients), SLC (8 patients) both from Hospital Regional (Malaga, Spain), and SCLC (14 patients) from EGA (European Genome Archive) with code EGAS00001000334. An automated workflow was designed for pre-processing, mapping against the human genome hg38, assessing differential expression, and sample comparison, taking into account that samples are matched by patient. Results: A total of 2853, 3686 and 4863 genes were differentially expressed in adenocarcinoma, SLC and SCLC, respectively. There are 933 genes having a similar expression in the three cancers. Among the genes with a specific expression in each cancer we have found: 5 genes in adenocarcinoma (C4BPB, IYD, MSLN, TMC5, TRDN), 4 in SLC (AZGP1, HSPB3, MSLN, TP63) and 11 in SCLC (ADCYAP1, AKR1C1, AKR1C2, AKR1C3, ALDH3A1, GPA33, LAMB3, MSLN, PRAME, TARP, TUBA1A). Also we have found a gene that is the most different among the three, MSLN, which presents a differential logFC2 of –6,42, –2,23 and 2,84 in adeno, SLC and SCLC, respectively. Conclusions: The specific differential expression of genes in three different lung cancers conform a set of putative biomarker genes with a possible use on future prognostic and diagnostic methods.

Introduction: Gene expression analysis need to use reference genes (RGs) to normalize the measurements. Ideally, a RG should be expressed in the same degree in all the studied tissues, that is why housekeeping genes usually are used. But it has been demonstrated that they are less invariant than what was thought. Objectives: To find a set of RGs in lung cancer. Methods: RNA-seq reads of healthy and tumoral samples from EGA (17 patients with small-cell lung cancer [SCLC]) and NCBI (50 patients with adenocarcinoma lung cancer) repositories were downloaded. Reads were processed with a novel algorithm developed by us based on the coefficient of variation (CV) to select the genes with a CV lower than 15% or 20%, and whose number of reads per transcript was higher than 10,000. Hence, the most stable RGs having the highest expression level were selected. Results: Using 10,000 reads and CV Conclusions: The set of reference genes has been extended in two lung cancers, which makes more detailed expression analysis possible.

[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., This research was supported by co-funding from the European Union through the ERDF 2014–2020 “Programa Operativo de Crecimiento Inteligente” to the projects RTA2013-00068-C03 and RTA2013-00023-C02 of the Spanish INIA; BFU2011-22779 and RECUPERA2020-3.1.4 from the Spanish MINECO, P11-CVI-7487 from the regional PAI and NEUMOSUR grant 12/2015 entitled “Expresión de retrotransposones en pacientes con adenocarcinoma intervenido. Comparación entre tejjido sano y tumoral”. Publication costs were funded by the mentioned grants

Chapel is a parallel programming language designed to improve the productivity and ease of use of conventional and parallel computers. This language currently delivers sub optimal performance when executing codes that perform global data re-allocation operations on distributed memory architectures. This is mainly due to data communication that is done without aggregation (one message for each remote array element). In this work, we analyze Chapel's standard Block and Cyclic distribution modules and optimize the communication routines for array assignments by performing aggregation. Thanks to the expressive power of Chapel, the compiler and runtime have enough information to do communication aggregation without user intervention. The runtime relies on the low-level GAS Net networking layer, whose versions of one-sided bulk put/get routines that support strides are particularly useful for us. Experimental results conducted on Hector (a Cray XE6) and Jaguar (Cray XK6)reveal that the implemented techniques can lead to significant reductions in communication time.

Tarsys is a video archive system which combines the flexible organization of multimedia databases, the efficiency of real-time filesystems and the scalability of tertiary storage (magnetic tape libraries and optical jukeboxes). Heavy data transfers over the network are usual between video servers and their clients. Tarsys reduces network traffic through the use of a remote manipulation protocol, so that only required fragments of multimedia data are transferred. Tarsys provides a suitable platform for the automatic extraction of content information from multimedia data. It also provides management of content based queries and efficient access to video fragments found by queries. These facilities in the access to archived videos make it ideal for large TV digital archives and scientific databases where is constitutes a platform for quick development of custom video analysis.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.