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Purpose: Antibodies against the lymphocyte PD-1 (aPD-1) receptor are cornerstone agents for advanced non–small cell lung cancer (NSCLC), based on their ability to restore the exhausted antitumor immune response. Our study reports a novel, lymphocyte-independent, therapeutic activity of aPD-1 against NSCLC, blocking the tumor-intrinsic PD-1 receptors on chemoresistant cells. Experimental Design: PD-1 in NSCLC cells was explored in vitro at baseline, including stem-like pneumospheres, and following treatment with cisplatin both at transcriptional and protein levels. PD-1 signaling and RNA sequencing were assessed. The lymphocyte-independent antitumor activity of aPD-1 was explored in vitro, by PD-1 blockade and stimulation with soluble ligand (PD-L1s), and in vivo within NSCLC xenograft models. Results: We showed the existence of PD-1+ NSCLC cell subsets in cell lines and large in silico datasets (Cancer Cell Line Encyclopedia and The Cancer Genome Atlas). Cisplatin significantly increased PD-1 expression on chemo-surviving NSCLC cells (2.5-fold P = 0.0014), while the sequential treatment with anti–PD-1 Ab impaired their recovery after chemotherapy. PD-1 was found to be associated with tumor stemness features. PD-1 expression was enhanced in NSCLC stem-like pneumospheres (P < 0.0001), significantly promoted by stimulation with soluble PD-L1 (+27% ± 4, P < 0.0001) and inhibited by PD-1 blockade (−30% ± 3, P < 0.0001). The intravenous monotherapy with anti–PD-1 significantly inhibited tumor growth of NSCLC xenografts in immunodeficient mice, without the contribution of the immune system, and delayed the occurrence of chemoresistance when combined with cisplatin. Conclusions: We report first evidence of a novel lymphocyte-independent activity of anti–PD-1 antibodies in NSCLC, capable of inhibiting chemo-surviving NSCLC cells and exploitable to contrast disease relapses following chemotherapy. See related commentary by Augustin et al., p. 505

PD-L1/2 and phospho-p38 MAPK expression in NSCLC cells. Tumor membrane expression of PD-L1 and PD-L2 in NSCLC cell lines was intensely enhanced by treatment with Interferon γ (n=9, PD-L1 p=0.02, PD-L2 p

Treatment with PD-L1s is associated with the up-regulation of expression of key protein coding genes involved in processes of tumorigenesis, EMT, tumor aggressiveness and chemoresistance. Heatmap showing z-scaled DESeq2-normalized expression values of the 14 differentially expressed genes between PD-L1s and untreated cells. Right annotation indicates the mean DESeq2-normalized gene expression values. Top annotations depict the pneumosphere of origin and the treatment. Hierarchical clustering of genes and samples is shown on the left and top, respectively (A). Volcano plot showing the log2 fold change (log2FC) and adjusted p-value values of all genes between PD-L1s and untreated samples. Differentially expressed genes are depicted in red (B).

Double positive OCT3/4-PD1 subsets in the bulk NSCLC cells after cisplatin treatment. OCT3/4 expression preferentially co-localized on PD-1+ NSCLC cells as compared with the PD-1- counterpart (14% vs 0.1%). Representative flow cytometry histograms of OCT3/4 expression are reported in figure.

HNRNPA2B1 is associated with prostate cancer (PC) disease aggressiveness and underlies pro-tumourigenic cellular stress responses. By analysing >500 PC transcriptomes, we reveal that HNRNPA2B1 over-expression is associated with poor patient prognosis and stress response pathways. These include the “protein processing in the endoplasmic reticulum” (ER) pathway, which incorporates the unfolded protein response (UPR). By RNA-sequencing of HNRNPA2B1-depleted cells PC cells, we identified HNRNPA2B1-mediated down-regulation of UPR genes including the master ER-stress sensor IRE1, which induces ER proteostasis. Consistent with IRE1 down-regulation in HNRNPA2B1-depleted cells, we observed reduced splicing of the IRE1-target and key UPR effector XBP1s. Furthermore, HNRNPA2B1 depletion up-regulates expression of the IRE1-dependent decay (RIDD) target gene BLOC1S1, which is degraded by activated IRE1. We identify a HNRNPA2B1-IRE1-XBP1-controlled four gene prognostic biomarker signature (HIX) which classifies a subgroup of primary PC patients at high risk of disease relapse. Pharmacological targeting of IRE1 attenuated HNRNAPA2-driven PC cell growth. Taken together, our data reveal a putative novel mechanism of UPR activation in PC by HNRNPA2B1, which may promote an IRE1-dependent yet potentially-targetable recurrent disease phenotype.

Heterogeneity is a fundamental feature of complex phenotypes. So far, genomic screenings have profiled thousands of samples providing insights into the transcriptome of the cell. However, disentangling the heterogeneity of these transcriptomic Big Data to identify defective biological processes remains challenging. Here we present GSECA, a method exploiting the bimodal behavior of RNA-sequencing gene expression profiles to identify altered gene sets in heterogeneous patient cohorts. Using simulated and experimental RNA-sequencing data sets, we show that GSECA provides higher performances than other available algorithms in detecting truly altered biological processes in large cohorts. Applied to 5941 samples from 14 different cancer types, GSECA correctly identified the alteration of the PI3K/AKT signaling pathway driven by the somatic loss of PTEN and verified the emerging role of PTEN in modulating immune-related processes. In particular, we showed that, in prostate cancer, PTEN loss appears to establish an immunosuppressive tumor microenvironment through the activation of STAT3, and low PTEN expression levels have a detrimental impact on patient disease-free survival. GSECA is available at https://github.com/matteocereda/GSECA.

Dysregulation of alternative splicing in prostate cancer is linked to transcriptional programs activated by AR, ERG, FOXA1, and MYC. Here, we show that FOXA1 functions as the primary orchestrator of alternative splicing dysregulation across 500 primary and metastatic prostate cancer transcriptomes. We demonstrate that FOXA1 binds to the regulatory regions of splicing-related genes, including HNRNPK and SRSF1. By controlling trans-acting factor expression, FOXA1 exploits an "exon definition" mechanism calibrating alternative splicing toward dominant isoform production. This regulation especially impacts splicing factors themselves and leads to a reduction of nonsense-mediated decay (NMD)-targeted isoforms. Inclusion of the NMD-determinant FLNA exon 30 by FOXA1-controlled oncogene SRSF1 promotes cell growth in vitro and predicts disease recurrence. Overall, we report a role for FOXA1 in rewiring the alternative splicing landscape in prostate cancer through a cascade of events from chromatin access, to splicing factor regulation, and, finally, to alternative splicing of exons influencing patient survival.

Simple Summary Prostate cancer research has been recently characterized by the discovery of several prognostic and predictive molecular factors, which ultimately improve patients’ management. In this review, we present the clinical impact of such factors and the methods to detect them, both on tissue and blood, in advanced prostate cancer patients. The aim of this review is ultimately to depict the role of these molecular factors in the era of precision oncology. Abstract Prostate cancer (PCa) therapy has been recently revolutionized by the approval of new therapeutic agents in the metastatic setting. However, the optimal therapeutic strategy in such patients should be individualized in the light of prognostic and predictive molecular factors, which have been recently studied: androgen receptor (AR) alterations, PTEN-PI3K-AKT pathway deregulation, homologous recombination deficiency (HRD), mismatch repair deficiency (MMRd), and tumor microenvironment (TME) modifications. In this review, we highlighted the clinical impact of prognostic and predictive molecular factors in PCa patients’ outcomes, identifying biologically distinct subtypes. We further analyzed the relevant methods to detect these factors, both on tissue, i.e., immunohistochemistry (IHC) and molecular tests, and blood, i.e., analysis of circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA). Moreover, we discussed the main pros and cons of such techniques, depicting their present and future roles in PCa management, throughout the precision medicine era.

Artificial intelligence, or the discipline of developing computational algorithms able to perform tasks that requires human intelligence, offers the opportunity to improve our idea and delivery of precision medicine. Here, we provide an overview of artificial intelligence approaches for the analysis of large-scale RNA-sequencing datasets in cancer. We present the major solutions to disentangle inter- and intra-tumor heterogeneity of transcriptome profiles for an effective improvement of patient management. We outline the contributions of learning algorithms to the needs of cancer genomics, from identifying rare cancer subtypes to personalizing therapeutic treatments.

Osteosarcoma (OS) is a rare bone malignant tumour with a poor prognosis in the case of recurrence. So far, there is no agreement on the best systemic therapy for relapsed OS. The availability of next generation sequencing techniques has recently revolutionized clinical research. The sequencing of the tumour and its matched normal counterpart has the potential to reveal a wide landscape of genetic alterations with significant implications for clinical practice. The knowledge that the genomic profile of a patient’s tumour can be precisely mapped and matched to a targeted therapy in real time has improved the development of precision medicine trials (PMTs). PMTs aiming at determining the effectiveness of targeted therapies could be advantageous for patients with a tumour refractory to standard therapies. Development of PMTs for relapsed OS is largely encouraging and is in its initial phase. Assessing OS features, such as its rarity, its age distribution, the technical issues related to the bone tissue origin, and its complex genomic landscape, represents a real challenge for PMTs development. In this light, a multidisciplinary approach is required to fully exploit the potential of precision medicine for OS patients.

The choroid is the vascular structure nourishing the retinal pigment epithelium and the outer retina and it plays a key role in the homeostasis of the eye both under physiological and pathological conditions. In the last 20 years we have moved from "guessing" what was happening beyond the retinal pigment epithelium to actually visualize structural and functional changes of the choroid in vivo noninvasively. In this review we describe the state of the art of choroidal imaging, focusing on the multiple techniques available in the clinical and research setting including indocyanine green angiography, labeled-cells angiographies, optical coherence tomography (OCT), enhanced depth imaging, swept source OCT, and OCT angiography. In the first section of the article, we describe their main applications and the basic principles to interpret the imaging results. Increasing evidence suggests that the choroid is much more involved than we used to think in many pathological conditions from uveitis to intraocular tumors, from vascular diseases to age-related macular degeneration. All clinicians should hence know which is the most appropriate imaging investigation to explore the choroid in the disease they are dealing with and how to interpret the results. For this reason the second section of this review summarizes the best imaging approach and the most common findings visible on choroidal imaging in different diseases of the eye.

Nowadays, intravitreal injections are the gold standard for the treatment of age-related macular degeneration (AMD). The prediction of the transport mechanism for the injected anti vascular endothelial growth factor (anti-VEGF) is needed in order to understand its distribution and consumption after each injection. Thus, this study aims at implementing a full model of vitreous drug delivery. The main novelty of this work is the coupling between an experimental evaluation of the scleral permeability and a numerical analysis of the saccadic dependency of the transport phenomena.

Ubiquitination is one of the main post-translational modification of proteins. It plays key roles in a broad range of cellular functions, including protein degradation, protein interactions, and subcellular location. In the ubiquitination system, different proteins are involved and their dysregulation can lead to various human diseases, including cancers. By using data available from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases, we here show that the ubiquitin conjugating enzyme, E2C (UBE2C), is overexpressed in all 27 cancers we investigated. UBE2C expression is significantly higher in late-stage tumors, which might indicate its involvement in tumor progression and invasion. This study also revealed that patients with higher UBE2C levels showed a shorter overall survival (OS) time and worse OS prognosis. Moreover, our data show that UBE2C higher-expression leads to worse disease-free survival prognosis (DFS), indicating that UBE2C overexpression correlates with poor clinical outcomes. We also identified genes with positive correlations with UBE2C in several cancers. We found a number of poorly studied genes (family with sequence similarity 72-member D, FAM72D, meiotic nuclear divisions 1, MND1, mitochondrial fission regulator 2, MTFR2, and POC1 centriolar protein A, POC1A) whose expression correlates with UBE2C. These genes might be considered as new targets for cancers therapies since they showed overexpression in several cancers and correlate with worse OS prognosis.

BACKGROUND: Next generation sequencing methods are widely adopted for a large amount of scientific purposes, from pure research to health-related studies. The decreasing costs per analysis led to big amounts of generated data and to the subsequent improvement of software for the respective analyses. As a consequence, many approaches have been developed to chain different software in order to obtain reliable and reproducible workflows. However, the large range of applications for NGS approaches entails the challenge to manage many different workflows without losing reliability.METHODS: We here present a high-throughput sequencing pipeline (HaTSPiL), a Python-powered CLI tool designed to handle different approaches for data analysis with a high level of reliability. The software relies on the barcoding of filenames using a human readable naming convention that contains any information regarding the sample needed by the software to automatically choose different workflows and parameters. HaTSPiL is highly modular and customisable, allowing the users to extend its features for any specific need.CONCLUSIONS: HaTSPiL is licensed as Free Software under the MIT license and it is available at https://github.com/dodomorandi/hatspil.

Prostate cancer (PCa) is genomically driven by dysregulation of transcriptional networks involving the transcriptional factors (TFs) FOXA1, ERG, AR, and HOXB13. However, the role of these specific TFs in the regulation of alternative pre-mRNA splicing (AS), which is a proven therapeutic vulnerability for cancers driven by the TF MYC, is not described. Using transcriptomic datasets from PCa patients, we tested for an association between expression of FOXA1, ERG, AR, HOXB13, and MYC, and genes involved in AS - termed splicing-related proteins (SRPs), which have pleiotropic roles in RNA metabolism. We identified FOXA1 as the strongest predictor of dysregulated SRP gene expression, which was associated with PCa disease relapse after treatment. Subsequently, we selected a subset of FOXA1-binding and actively-transcribed SRP genes that phenocopy the FOXA1 dependency of PCa cells, and confirmed in vitro via knockdown and over-expression that FOXA1 regulates SRP gene expression. Finally, we demonstrated the persistence of a FOXA1-SRP gene association in treatment-relapsed castration-resistant PCa (CRPCa) patients. Our data demonstrate, for the first time, that FOXA1 controls dysregulated SRP gene expression, which is associated with poor PCa patient outcomes. Analogous to MYC-driven cancers, our findings implicate the therapeutic targeting of SRPs and AS in FOXA1-overexpressing PCa.

Summary Detecting significant associations between genetic variants and disease may prove particularly challenging when the variants are rare in the population and/or act together with other variants to cause the disease. We have developed a statistical framework named Mutation Enrichment Gene set Analysis of Variants (MEGA-V) that specifically detects the enrichments of genetic alterations within a process in a cohort of interest. By focusing on the mutations of several genes contributing to the same function rather than on those affecting a single gene, MEGA-V increases the power to detect statistically significant associations. Availability and Implementation MEGA-V is available at https://github.com/ciccalab/MEGA Supplementary information Supplementary data are available at Bioinformatics online.

Summary Cancer genetic heterogeneity offers a wide repertoire of molecular determinants to be screened as therapeutic targets. Here, we identify potential anticancer targets by exploiting negative genetic interactions between genes with driver loss-of-function mutations (recessive cancer genes) and their functionally redundant paralogs. We identify recessive genes with additional copies and experimentally test our predictions on three paralogous pairs. We confirm digenic negative interactions between two cancer genes ( SMARCA4 and CDH1 ) and their corresponding paralogs ( SMARCA2 and CDH3 ). Furthermore, we identify a trigenic negative interaction between the cancer gene DNMT3A , its functional paralog DNMT3B , and a third gene, DNMT1 , which encodes the only other human DNA-methylase domain. Although our study does not exclude other causes of synthetic lethality, it suggests that functionally redundant paralogs of cancer genes could be targets in anticancer therapy.

Cohesin is a multi-protein complex that tethers sister chromatids during mitosis and mediates DNA repair, genome compartmentalisation and regulation of gene expression. Cohesin subunits frequently acquire cancer loss-of-function alterations and act as tumour suppressors in several tumour types. This has led to increased interest in cohesin as potential target in anti-cancer therapy. Here we show that the loss-of-function of STAG2, a core component of cohesin and an emerging tumour suppressor, leads to synthetic dependency of mutated cancer cells on its paralog STAG1. STAG1 and STAG2 share high sequence identity, encode mutually exclusive cohesin subunits and retain partially overlapping functions. We inhibited STAG1 and STAG2 in several cancer cell lines where the two genes have variable mutation and copy number status. In all cases, we observed that the simultaneous blocking of STAG1 and STAG2 significantly reduces cell proliferation. We further confirmed the synthetic lethal interaction developing a vector-free CRISPR system to induce STAG1/STAG2 double gene knockout. We provide strong evidence that STAG1 is a promising therapeutic target in cancers with inactivating alterations of STAG2.

Cancer genomes acquire somatic alterations that largely differ between and within cancer types. Several of these alterations inactivate genes that are normally functional with no deleterious consequences on cancer cells due to genetic redundancy. Here we discuss how this leads to cancer synthetic dependencies that can be exploited in therapy.

TDP-43 is a predominantly nuclear RNA-binding protein that forms inclusion bodies in frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS). The mRNA targets of TDP-43 in the human brain and its role in RNA processing are largely unknown. Using individual nucleotide-resolution ultraviolet cross-linking and immunoprecipitation (iCLIP), we found that TDP-43 preferentially bound long clusters of UG-rich sequences in vivo. Analysis of RNA binding by TDP-43 in brains from subjects with FTLD revealed that the greatest increases in binding were to the MALAT1 and NEAT1 noncoding RNAs. We also found that binding of TDP-43 to pre-mRNAs influenced alternative splicing in a similar position-dependent manner to Nova proteins. In addition, we identified unusually long clusters of TDP-43 binding at deep intronic positions downstream of silenced exons. A substantial proportion of alternative mRNA isoforms regulated by TDP-43 encode proteins that regulate neuronal development or have been implicated in neurological diseases, highlighting the importance of TDP-43 for the regulation of splicing in the brain.

Summary: We propose a C++ class library developed to the purpose of making the implementation of sequence analysis algorithms easier and faster when genomic annotations and variations need to be considered. The library provides a class hierarchy to seamlessly bind together annotations of genomic elements to sequences and to algorithm results; it allows to evaluate the effect of mutations/variations in terms of both element position shifts and of algorithm results, limiting recalculation to the minimum. Particular care has been posed to keep memory and time overhead into acceptable limits. Availability and Implementation: A complete tutorial as well as a detailed doxygen generated documentation and source code is freely available at http://bioinformatics.emedea.it/geco, under the GPL license. The library was written in standard ISO C++, and does not depend on external libraries. Contact: uberto.pozzoli@bp.lnf.it

Background Mismatch repair deficient colorectal adenomas are composed of transformed cells that descend from a common founder and progressively accumulate genomic alterations. The proliferation history of these tumors is still largely unknown. Here we present a novel approach to rebuild the proliferation trees that recapitulate the history of individual colorectal adenomas by mapping the progressive acquisition of somatic point mutations during tumor growth. Results Using our approach, we called high and low frequency mutations acquired in the X chromosome of four mismatch repair deficient colorectal adenomas deriving from male individuals. We clustered these mutations according to their frequencies and rebuilt the proliferation trees directly from the mutation clusters using a recursive algorithm. The trees of all four lesions were formed of a dominant subclone that co-existed with other genetically heterogeneous subpopulations of cells. However, despite this similar hierarchical organization, the growth dynamics varied among and within tumors, likely depending on a combination of tumor-specific genetic and environmental factors. Conclusions Our study provides insights into the biological properties of individual mismatch repair deficient colorectal adenomas that may influence their growth and also the response to therapy. Extended to other solid tumors, our novel approach could inform on the mechanisms of cancer progression and on the best treatment choice. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0437-8) contains supplementary material, which is available to authorized users.

BackgroundThe vasopressin receptor type 1b (AVPR1B) is mainly expressed by pituitary corticotropes and it mediates the stimulatory effects of AVP on ACTH release; commonAVPR1Bhaplotypes have been involved in mood and anxiety disorders in humans, while rodents lacking a functional receptor gene display behavioral defects and altered stress responses.ResultsHere we have analyzed the two exons of the gene and the data we present suggest thatAVPR1Bhas been subjected to natural selection in humans. In particular, analysis of exon 2 strongly suggests the action of balancing selection in African populations and Europeans: the region displays high nucleotide diversity, an excess of intermediate-frequency alleles, a higher level of within-species diversity compared to interspecific divergence and a genealogy with common haplotypes separated by deep branches. This relatively unambiguous situation coexists with unusual features across exon 1, raising the possibility that a nonsynonymous variant (Gly191Arg) in this region has been subjected to directional selection.ConclusionAlthough the underlying selective pressure(s) remains to be identified, we consider this to be among the first documented examples of a gene involved in mood disorders and subjected to natural selection in humans; this observation might add support to the long-debated idea that depression/low mood might have played an adaptive role during human evolution.

Background Mammalian genomes consist of regions differing in GC content, referred to as isochores or GC-content domains. The scientific debate is still open as to whether such compositional heterogeneity is a selected or neutral trait. Results Here we analyze SNP allele frequencies, retrotransposon insertion polymorphisms (RIPs), as well as fixed substitutions accumulated in the human lineage since its divergence from chimpanzee to indicate that biased gene conversion (BGC) has been playing a role in within-genome GC content variation. Yet, a distinct contribution to GC content evolution is accounted for by a selective process. Accordingly, we searched for independent evidences that GC content distribution does not conform to neutral expectations. Indeed, after correcting for possible biases, we show that intron GC content and size display isochore-specific correlations. Conclusion We consider that the more parsimonious explanation for our results is that GC content is subjected to the action of both weak selection and BGC in the human genome with features such as nucleosome positioning or chromatin conformation possibly representing the final target of selective processes. This view might reconcile previous contrasting findings and add some theoretical background to recent evidences suggesting that GC content domains display different behaviors with respect to highly regulated biological processes such as developmentally-stage related gene expression and programmed replication timing during neural stem cell differentiation.

Transposable elements (TEs) represent more than 45% of the human and mouse genomes. Both parasitic and mutualistic features have been shown to apply to the host-TE relationship but a comprehensive scenario of the forces driving TE fixation within mammalian genes is still missing. We show that intronic multispecies conserved sequences (MCSs) have been affecting TE integration frequency over time. We verify that a selective economizing pressure has been acting on TEs to decrease their frequency in highly expressed genes. After correcting for GC content, MCS density and intron size, we identified TE-enriched and TE-depleted gene categories. In addition to developmental regulators and transcription factors, TE-depleted regions encompass loci that might require subtle regulation of transcript levels or precise activation timing, such as growth factors, cytokines, hormones, and genes involved in the immune response. The latter, despite having reduced frequencies of most TE types, are significantly enriched in mammalian-wide interspersed repeats (MIRs). Analysis of orthologous genes indicated that MIR over-representation also occurs in dog and opossum immune response genes, suggesting, given the partially independent origin of MIR sequences in eutheria and metatheria, the evolutionary conservation of a specific function for MIRs located in these loci. Consistently, the core MIR sequence is over-represented in defense response genes compared to the background intronic frequency. Our data indicate that gene function, expression level, and sequence conservation influence TE insertion/fixation in mammalian introns. Moreover, we provide the first report showing that a specific TE family is evolutionarily associated with a gene function category.

Background Duchenne and Becker Muscular dystrophies (DMD/BMD) are allelic disorders caused by mutations in the dystrophin gene, which encodes a sarcolemmal protein responsible for muscle integrity. Deletions and duplications account for approximately 75% of mutations in DMD and 85% in BMD. The implementation of techniques allowing complete gene sequencing has focused attention on small point mutations and other mechanisms underlying complex rearrangements. Methods We selected 47 patients (41 families; 35 DMD, 6 BMD) without deletions and duplications in DMD gene (excluded by multiplex ligation-dependent probe amplification and multiplex polymerase chain reaction analysis). This cohort was investigated by systematic direct sequence analysis to study sequence variation. We focused our attention on rare mutational events which were further studied through transcript analysis. Results We identified 40 different nucleotide alterations in DMD gene and their clinical correlates; altogether, 16 mutations were novel. DMD probands carried 9 microinsertions/microdeletions, 19 nonsense mutations, and 7 splice-site mutations. BMD patients carried 2 nonsense mutations, 2 splice-site mutations, 1 missense substitution, and 1 single base insertion. The most frequent stop codon was TGA (n = 10 patients), followed by TAG (n = 7) and TAA (n = 4). We also analyzed the molecular mechanisms of five rare mutational events. They are two frame-shifting mutations in the DMD gene 3'end in BMD and three novel splicing defects: IVS42: c.6118-3C>A, which causes a leaky splice-site; c.9560A>G, which determines a cryptic splice-site activation and c.9564-426 T>G, which creates pseudoexon retention within IVS65. Conclusion The analysis of our patients' sample, carrying point mutations or complex rearrangements in DMD gene, contributes to the knowledge on phenotypic correlations in dystrophinopatic patients and can provide a better understanding of pre-mRNA maturation defects and dystrophin functional domains. These data can have a prognostic relevance and can be useful in directing new therapeutic approaches, which rely on a precise definition of the genetic defects as well as their molecular consequences.