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Biomedical subjects

Daniel Gautheret

Publications and source records attributed to Daniel Gautheret.

13 recordsLinked to original sources

Role of ctDNA Tumor Fraction in Selecting Immunotherapy-Based Regimens in Advanced Non-Small Cell Lung Cancer.

PURPOSE: Immune checkpoint blockers (ICB) have transformed advanced non-small cell lung cancer (aNSCLC) treatment, but identifying patients who benefit from adding chemotherapy remains challenging, especially in PD-L1 &#x2265; 50%. PD-L1 is an imperfect biomarker, highlighting the need for better selection tools. EXPERIMENTAL DESIGN: Liquid biopsy (LBx) assessment was performed using hybrid capture-based next-generation sequencing of plasma cell-free DNA. LBx data, molecular profile, and clinicopathologic data were collected. The predictive and prognostic values of tumor fraction (TF) were assessed using a deidentified nationwide (US-based) NSCLC clinicogenomic database [Clinico-Genomic Database (CGDB)]. An independent cohort with aNSCLC from Gustave Roussy was used to validate the findings and to study the correlation of circulating tumor DNA (ctDNA) TF and total metabolic tumor volume and its molecular correlates. RESULTS: In the CGDB database (n = 965), elevated ctDNA TF was prognostic for worse outcomes on ICBs and, when &#x2265;5%, predictive of benefit from ICB + chemotherapy [HR for real-world progression-free survival 0.58 (0.41-0.82); P = 0.002]. The 5% cutoff for TF was validated in an independent cohort from Gustave Roussy. In 283 patients with paired PET scans, ctDNA TF correlated with metabolic tumor volume (rho = 0.46; P < 0.001) and was influenced by TP53/RB1 mutations. CONCLUSIONS: ctDNA TF integrates disease burden and biology. Patients with high ctDNA TF derive greater benefit from chemoimmunotherapy, supporting its use as a biomarker to guide treatment intensification.

Humans↗

The disparate nature of "intergenic" polyadenylation sites.

The termination of mature eukaryotic mRNAs occurs at specific polyadenylation sites located downstream from stop codons in the 3'-untranslated region (UTR). An accurate delineation of these sites is essential for the study of 3'-UTR-based gene regulation and for the design of pertinent probes for transcriptome analysis. Although typical poly(A) sites are located between 0 and 2 kb from the stop codon, EST sequence analyses have identified sites located at unexpectedly long ranges (5-10 kb) in a number of genes. Here we perform a complete mapping of EST and full-length cDNA sequences on the mouse and human genome to observe putative poly(A) sites extending beyond annotated 3'-ends and into the intergenic regions. We introduce several quality parameters for poly(A) site prediction and train a classification tree to associate P-values to predicted sites. We observe a higher than background level of high-scoring sites up to 12-15 kb past the stop codon, both in human and mouse. This leads to an estimate of about 5000 human genes having unreported 3'-end extensions and about 3500 novel polyadenylated transcripts lying in present "intergenic" regions. These high-scoring, long-range poly(A) sites corresponding to novel transcripts and gene extensions should be incorporated into current human and mouse gene repositories.

3' Untranslated Regions↗

Conservation of alternative polyadenylation patterns in mammalian genes.

BACKGROUND: Alternative polyadenylation is a widespread mechanism contributing to transcript diversity in eukaryotes. Over half of mammalian genes are alternatively polyadenylated. Our understanding of poly(A) site evolution is limited by the lack of a reliable identification of conserved, equivalent poly(A) sites among species. We introduce here a working definition of conserved poly(A) sites as sites that are both (i) properly aligned in human and mouse orthologous 3' untranslated regions (UTRs) and (ii) supported by EST or cDNA data in both species. RESULTS: We identified about 4800 such conserved poly(A) sites covering one third of the orthologous gene set studied. Characteristics of conserved poly(A) sites such as processing efficiency and tissue-specificity were analyzed. Conserved sites show a higher processing efficiency but no difference in tissular distribution when compared to non-conserved sites. In general, alternative poly(A) sites are species-specific and involve minor, non-conserved sites that are unlikely to play essential roles. However, there are about 500 genes with conserved tandem poly(A) sites. A significant fraction of these conserved tandems display a conserved arrangement of major/minor sites in their 3' UTR, suggesting that these alternative 3' ends may be under selection. CONCLUSION: This analysis allows us to identify potential functional alternative poly(A) sites and provides clues on the selective mechanisms at play in the appearance of multiple poly(A) sites and their maintenance in the 3' UTRs of genes.

3' Untranslated Regions↗

Differential repression of alternative transcripts: a screen for miRNA targets.

Alternative polyadenylation sites produce transcript isoforms with 3' untranslated regions (UTRs) of different lengths. If a microRNA (miRNA) target is present in the UTR, then only those target-containing isoforms should be sensitive to control by a cognate miRNA. We carried out a systematic examination of 3' UTRs containing multiple poly(A) sites and putative miRNA targets. Based on expressed sequence tag (EST) counts and EST library information, we observed that levels of isoforms containing targets for miR-1 or miR-124, two miRNAs causing downregulation of transcript levels, were reduced in tissues expressing the corresponding miRNA. This analysis was repeated for all conserved 7-mers in 3' UTRs, resulting in a selection of 312 motifs. We show that this set is significantly enriched in known miRNA targets and mRNA-destabilizing elements, which validates our initial hypothesis. We scanned the human genome for possible cognate miRNAs and identified phylogenetically conserved precursors matching our motifs. This analysis can help identify target-miRNA couples that went undetected in previous screens, but it may also reveal targets for other types of regulatory factors.

Animals↗

AltTrans: transcript pattern variants annotated for both alternative splicing and alternative polyadenylation.

BACKGROUND: The three major mechanisms that regulate transcript formation involve the selection of alternative sites for transcription start (TS), splicing, and polyadenylation. Currently there are efforts that collect data & annotation individually for each of these variants. It is important to take an integrated view of these data sets and to derive a data set of alternate transcripts along with consolidated annotation. We have been developing in the past computational pipelines that generate value-added data at genome-scale on individual variant types; these include AltSplice on splicing and AltPAS on polyadenylation. We now extend these pipelines and integrate the resultant data sets to facilitate an integrated view of the contributions from splicing and polyadenylation in the formation of transcript variants. DESCRIPTION: The AltSplice pipeline examines gene-transcript alignments and delineates alternative splice events and splice patterns; this pipeline is extended as AltTrans to delineate isoform transcript patterns for each of which both introns/exons and 'terminating' polyA site are delineated; EST/mRNA sequences that qualify the transcript pattern confirm both the underlying splicing and polyadenylation. The AltPAS pipeline examines gene-transcript alignments and delineates all potential polyA sites irrespective of underlying splicing patterns. Resultant polyA sites from both AltTrans and AltPAS are merged. The generated database reports data on alternative splicing, alternative polyadenylation and the resultant alternate transcript patterns; the basal data is annotated for various biological features. The data (named as integrated AltTrans data) generated for both the organisms of human and mouse is made available through the Alternate Transcript Diversity web site at http://www.ebi.ac.uk/atd/. CONCLUSION: The reported data set presents alternate transcript patterns that are annotated for both alternative splicing and alternative polyadenylation. Results based on current transcriptome data indicate that the contribution of alternative splicing is larger than that of alternative polyadenylation.

Alternative Splicing↗

Computing expectation values for RNA motifs using discrete convolutions.

BACKGROUND: Computational biologists use Expectation values (E-values) to estimate the number of solutions that can be expected by chance during a database scan. Here we focus on computing Expectation values for RNA motifs defined by single-strand and helix lod-score profiles with variable helix spans. Such E-values cannot be computed assuming a normal score distribution and their estimation previously required lengthy simulations. RESULTS: We introduce discrete convolutions as an accurate and fast mean to estimate score distributions of lod-score profiles. This method provides excellent score estimations for all single-strand or helical elements tested and also applies to the combination of elements into larger, complex, motifs. Further, the estimated distributions remain accurate even when pseudocounts are introduced into the lod-score profiles. Estimated score distributions are then easily converted into E-values. CONCLUSION: A good agreement was observed between computed E-values and simulations for a number of complete RNA motifs. This method is now implemented into the ERPIN software, but it can be applied as well to any search procedure based on ungapped profiles with statistically independent columns.

Algorithms↗

Profile-based detection of microRNA precursors in animal genomes.

MOTIVATION: MicroRNAs (miRNA) are essential 21-22 nt regulatory RNAs produced from larger hairpin-like precursors. Local sequence alignment tools such as BLAST are able to identify new members of known miRNA families, but not all of them. We set out to estimate how many new miRNAs could be recovered using a profile-based strategy such as that implemented in the ERPIN program. RESULTS: We constructed alignments for 18 miRNA families and performed ERPIN searches on animal genomes. Results were compared to those of a WU-BLAST search at the same E-value cutoff. The two combined approaches produced 265 new miRNA candidates that were not found in miRNA databases. About 17% of hits were ERPIN specific. They showed better structural characteristics than BLAST-specific hits and included interesting candidates such as members of the miR-17 cluster in Tetraodon. Profile-based RNA detection will be an important complement of similarity search programs in the completion of miRNA collections.

Algorithms↗

The ERPIN server: an interface to profile-based RNA motif identification.

ERPIN is an RNA motif identification program that takes an RNA sequence alignment as an input and identifies related sequences using a profile-based dynamic programming algorithm. ERPIN differs from other RNA motif search programs in its ability to capture subtle biases in the training set and produce highly specific and sensitive searches, while keeping CPU requirements at a practical level. In its latest version, ERPIN also computes E-values, which tell biologists how likely they are to encounter a specific sequence match by chance-a useful indication of biological significance. We present here the ERPIN online search interface (http://tagc.univ-mrs.fr/erpin/). This web server automatically performs ERPIN searches for different RNA genes or motifs, using predefined training sets and search parameters. With a couple of clicks, users can analyze an entire bacterial genome or a genomic segment of up to 5Mb for the presence of tRNAs, 5S rRNAs, SRP RNA, C/D box snoRNAs, hammerhead motifs, miRNAs and other motifs. Search results are displayed with sequence, score, position, E-value and secondary structure graphics. An example of a complete genome scan is provided, as well as an evaluation of run times and specificity/sensitivity information for all available motifs.

Internet↗

Sequence determinants in human polyadenylation site selection.

BACKGROUND: Differential polyadenylation is a widespread mechanism in higher eukaryotes producing mRNAs with different 3' ends in different contexts. This involves several alternative polyadenylation sites in the 3' UTR, each with its specific strength. Here, we analyze the vicinity of human polyadenylation signals in search of patterns that would help discriminate strong and weak polyadenylation sites, or true sites from randomly occurring signals. RESULTS: We used human genomic sequences to retrieve the region downstream of polyadenylation signals, usually absent from cDNA or mRNA databases. Analyzing 4956 EST-validated polyadenylation sites and their -300/+300 nt flanking regions, we clearly visualized the upstream (USE) and downstream (DSE) sequence elements, both characterized by U-rich (not GU-rich) segments. The presence of a USE and a DSE is the main feature distinguishing true polyadenylation sites from randomly occurring A(A/U)UAAA hexamers. While USEs are indifferently associated with strong and weak poly(A) sites, DSEs are more conspicuous near strong poly(A) sites. We then used the region encompassing the hexamer and DSE as a training set for poly(A) site identification by the ERPIN program and achieved a prediction specificity of 69 to 85% for a sensitivity of 56%. CONCLUSION: The availability of complete genomes and large EST sequence databases now permit large-scale observation of polyadenylation sites. Both U-rich sequences flanking both sides of poly(A) signals contribute to the definition of "true" sites. However, the downstream U-rich sequences may also play an enhancing role. Based on this information, poly(A) site prediction accuracy was moderately but consistently improved compared to the best previously available algorithm.

3' Flanking Region↗

Expression profiling in mouse fetal thymus reveals clusters of coordinately expressed genes that mark individual stages of T-cell ontogeny.

To search for genes that participate in regulatory networks sustaining mouse embryonic T-cell development, we have performed expression profiling using nylon macroarrays. Labeled samples representative of individual developmental stages were utilized, taking advantage of cell homogeneity during early thymus ontogeny. cDNAs revealing differential expression were further selected using labeled samples derived from lymphoid versus non-lymphoid tissues, and from mutant thymi exhibiting T-cell developmental defects. We thus identified clusters of coexpressed genes during T-cell embryogenesis and characterized their sequences through bioinformatics. We compare our results with those from other profiling analyses in the immune system, and discuss their implications for the definition of genes whose products are involved in T-cell development.

Animals↗

A survey of metazoan selenocysteine insertion sequences.

The computational detection of novel selenoproteins in genomic sequences is usually achieved through identification of SECIS, a conserved secondary structure element found in the 3' UTR of animal selenoprotein mRNAs. Previous studies have used "descriptors" specifying the number of base pairs and the conserved nucleotides in SECIS to identify this element. A major drawback of the "descriptor" approach is that the number of detections in current genomic or transcript databases largely exceeds the number of true selenoproteins. In this study, we use instead the ERPIN program to detect SECIS elements. ERPIN is based on a lod-score profile algorithm that uses a training-set of aligned RNA sequences as input. From an initial alignment of 44 animal SECIS sequences, we performed a series of iterative searches in which the training set was progressively enriched up to 117 confirmed SECIS elements, from a large collection of metazoan species. About 200 high-scoring candidates were also detected. We show that ERPIN scores for these candidates can be converted into expect values, thus enabling their statistical evaluation. The most interesting SECIS candidates are presented.

Animals↗

RNAML: a standard syntax for exchanging RNA information.

Analyzing a single data set using multiple RNA informatics programs often requires a file format conversion between each pair of programs, significantly hampering productivity. To facilitate the interoperation of these programs, we propose a syntax to exchange basic RNA molecular information. This RNAML syntax allows for the storage and the exchange of information about RNA sequence and secondary and tertiary structures. The syntax permits the description of higher level information about the data including, but not restricted to, base pairs, base triples, and pseudoknots. A class-oriented approach allows us to represent data common to a given set of RNA molecules, such as a sequence alignment and a consensus secondary structure. Documentation about experiments and computations, as well as references to journals and external databases, are included in the syntax. The chief challenge in creating such a syntax was to determine the appropriate scope of usage and to ensure extensibility as new needs will arise. The syntax complies with the eXtensible Markup Language (XML) recommendations, a widely accepted standard for syntax specifications. In addition to the various generic packages that exist to read and interpret XML formats, an XML processor was developed and put in the open-source MC-Core library for nucleic acid and protein structure computer manipulation.

Databases, Nucleic Acid↗