MOREOVER: multiomics MR-guided radiotherapy optimization in locally advanced rectal cancer.

BACKGROUND: Complete response prediction in locally advanced rectal cancer (LARC) patients is generally focused on the radiomics analysis of staging MRI. Until now, omics information extracted from gut microbiota and circulating tumor DNA (ctDNA) have not been integrated in composite biomarkers-based models, thereby omitting valuable information from the decision-making process. In this study, we aim to integrate radiomics with gut microbiota and ctDNA-based genomics tracking during neoadjuvant chemoradiotherapy (nCRT). METHODS: The main hypothesis of the MOREOVER study is that the incorporation of composite biomarkers with radiomics-based models used in the THUNDER-2 trial will improve the pathological complete response (pCR) predictive power of such models, paving the way for more accurate and comprehensive personalized treatment approaches. This is due to the inclusion of actionable omics variables that may disclose previously unknown correlations with radiomics. Aims of this study are: - to generate longitudinal microbiome data linked to disease resistance to nCRT and postulate future therapeutic strategies in terms of both type of treatment and timing, such as fecal microbiota transplant in non-responding patients. - to describe the genomics pattern and ctDNA data evolution throughout the nCRT treatment in order to support the prediction outcome and identify new risk-category stratification agents. - to mine and combine collected data through integrated multi-omics approaches (radiomics, metagenomics, metabolomics, metatranscriptomics, human genomics, ctDNA) in order to increase the performance of the radiomics-based response predictive model for LARC patients undergoing nCRT on MR-Linac. EXPERIMENTAL DESIGN: The objective of the MOREOVER project is to enrich the phase II THUNDER-2 trial (NCT04815694) with gut microbiota and ctDNA omics information, by exploring the possibility to enhance predictive performance of the developed model. Longitudinal ctDNA genomics, microbiome and genomics data will be analyzed on 7 timepoints: prior to nCRT, during nCRT on a weekly basis and prior to surgery. Specific modelling will be performed for data harvested, according to the TRIPOD statements. DISCUSSION: We expect to find differences in fecal microbiome, ctDNA and radiomics profiles between the two groups of patients (pCR and not pCR). In addition, we expect to find a variability in the stability of the considered omics features over time. The identified profiles will be inserted into dedicated modelling solutions to set up a multiomics decision support system able to achieve personalized treatments.

MYC up-regulation confers vulnerability to dual inhibition of CDK12 and CDK13 in high-risk Group 3 medulloblastoma.

BACKGROUND: Medulloblastoma (MB) is the most common cerebellar malignancy during childhood. Among MB, MYC-amplified Group 3 tumors display the worst prognosis. MYC is an oncogenic transcription factor currently thought to be undruggable. Nevertheless, targeting MYC-dependent processes (i.e. transcription and RNA processing regulation) represents a promising approach. METHODS: We have tested the sensitivity of MYC-driven Group 3 MB cells to a pool of transcription and splicing inhibitors that display a wide spectrum of targets. Among them, we focus on THZ531, an inhibitor of the transcriptional cyclin-dependent kinases (CDK) 12 and 13. High-throughput RNA-sequencing analyses followed by bioinformatics and functional analyses were carried out to elucidate the molecular mechanism(s) underlying the susceptibility of Group 3 MB to CDK12/13 chemical inhibition. Data from International Cancer Genome Consortium (ICGC) and other public databases were mined to evaluate the functional relevance of the cellular pathway/s affected by the treatment with THZ531 in Group 3 MB patients. RESULTS: We found that pharmacological inhibition of CDK12/13 is highly selective for MYC-high Group 3 MB cells with respect to MYC-low MB cells. We identified a subset of genes enriched in functional terms related to the DNA damage response (DDR) that are up-regulated in Group 3 MB and repressed by CDK12/13 inhibition. Accordingly, MYC- and CDK12/13-dependent higher expression of DDR genes in Group 3 MB cells limits the toxic effects of endogenous DNA lesions in these cells. More importantly, chemical inhibition of CDK12/13 impaired the DDR and induced irreparable DNA damage exclusively in MYC-high Group 3 MB cells. The augmented sensitivity of MYC-high MB cells to CDK12/13 inhibition relies on the higher elongation rate of the RNA polymerase II in DDR genes. Lastly, combined treatments with THZ531 and DNA damage-inducing agents synergically suppressed viability of MYC-high Group 3 MB cells. CONCLUSIONS: Our study demonstrates that CDK12/13 activity represents an exploitable vulnerability in MYC-high Group 3 MB and may pave the ground for new therapeutic approaches for this high-risk brain tumor.

Identification by Exome Sequencing of Predisposing Variants in Familial Cases of Autoinflammatory Recurrent Fevers.

Periodic fever syndromes include autoinflammatory disorders (AID) that involve innate immunity. These disorders are characterized by recurrent fevers and aberrant multi-organ inflammation, without any involvement of T or B cells or the presence of autoantibodies. A complex genetic architecture has been recognized for many AID. However, this complexity has only been partially uncovered for familial Mediterranean fever and other conditions that have a classical monogenic origin and Mendelian transmission. Several gene panels are currently available for molecular diagnosis in patients suspected of having AID. However, even when an extensive number of genes (up to 50-100) are tested in a cohort of clinically selected patients, the diagnostic yield of AID ranges between 15% and 25%, depending on the clinical criteria used for patient selection. In the remaining 75-85% of cases, it is conceivable that the causative gene or genes responsible for a specific condition are still elusive. In these cases, the disease could be explained by variants, either recessive or dominant, that have a major effect on unknown genes, or by the cumulative impact of different variants in more than one gene, each with minor additive effects. In this study, we focused our attention on five familial cases of AID presenting with classical autosomal dominant transmission. To identify the probable monogenic cause, we performed exome sequencing. Through prioritization, filtering, and segregation analysis, we identified a few variants for each family. Subsequent bioinformatics evaluation and pathway analysis helped to narrow down the best candidate genes for each family to FCRL6, PKN1, STAB1, PTDGR, and VCAM1. Future studies on larger cohorts of familial cases will help confirm the pathogenic role of these genes in the pathogenesis of these complex disorders.

Unexpected finding of a rare pathogenic germline BRCA1 variant in an intrahepatic cholangiocarcinoma using the Oncomine Focus DNA assay: clinical and diagnostic implications.

BACKGROUND: Cholangiocarcinoma (CCA) is a malignant tumor arising from the epithelial cells of the bile ducts and is the second most common liver cancer after hepatocellular carcinoma. Recently, our Institution launched a Comprehensive Genomic Profiling (CGP) program (named FPG500 program), set up to provide a complete molecular characterization through the TruSight Oncology 500 High Throughput (TSO500HT) solution and samples that do not reach pre-set sample quantity and/or quality thresholds required for TSO500HT, are addressed to Oncomine Focus DNA Assay (OFA) and the Archer's FusionPlex Lung Panel (AFL). METHODS AND RESULTS: Here we report the case of a patient with iCCA enrolled in the FPG500 program and screened by the orthogonal workflow (OFA/AFL). Although BRCA1 is not among the genes declared in the OFA panel, we unexpectedly detected a pathogenic variant in this gene (c.5278-2del, rs878853285). CONCLUSIONS: This case highlights the diagnostic capabilities of CGP, now widely used in both clinical practice and academic setting. The incidental involvement of BRCA1 focuses attention on the role of BRCA genes in biliary tract cancers. Finally, as an orthogonal test confirmed the germline origin of BRCA1 c.5278-2del variant, the germline implications of CGP need to be considered.

Evaluating the Risk of Inguinal Lymph Node Metastases before Surgery Using the Morphonode Predictive Model: A Prospective Diagnostic Study in Vulvar Cancer Patients.

Ultrasound examination is an accurate method in the preoperative evaluation of the inguinofemoral lymph nodes when performed by experienced operators. The purpose of the study was to build a robust, multi-modular model based on machine learning to discriminate between metastatic and non-metastatic inguinal lymph nodes in patients with vulvar cancer. One hundred and twenty-seven women were selected at our center from March 2017 to April 2020, and 237 inguinal regions were analyzed (75 were metastatic and 162 were non-metastatic at histology). Ultrasound was performed before surgery by experienced examiners. Ultrasound features were defined according to previous studies and collected prospectively. Fourteen informative features were used to train and test the machine to obtain a diagnostic model (Morphonode Predictive Model). The following data classifiers were integrated: (I) random forest classifiers (RCF), (II) regression binomial model (RBM), (III) decisional tree (DT), and (IV) similarity profiling (SP). RFC predicted metastatic/non-metastatic lymph nodes with an accuracy of 93.3% and a negative predictive value of 97.1%. DT identified four specific signatures correlated with the risk of metastases and the point risk of each signature was 100%, 81%, 16% and 4%, respectively. The Morphonode Predictive Model could be easily integrated into the clinical routine for preoperative stratification of vulvar cancer patients.

BORN study: a multicenter randomized trial investigating cord blood red blood cell transfusions to reduce the severity of retinopathy of prematurity in extremely low gestational age neonates.

BACKGROUND: Extremely low gestational age neonates (ELGANs, i.e., neonates born before 28 weeks of gestation) are at high risk of developing retinopathy of prematurity (ROP), with potential long-life visual impairment. Due to concomitant anemia, ELGANs need repeated red blood cell (RBC) transfusions. These produce a progressive replacement of fetal hemoglobin (HbF) by adult hemoglobin (HbA). Furthermore, a close association exists between low levels of HbF and severe ROP, suggesting that a perturbation of the HbF-mediated oxygen release may derange retinal angiogenesis and promote ROP. METHODS/DESIGN: BORN (umBilical blOod to tRansfuse preterm Neonates) is a multicenter double-blinded randomized controlled trial in ELGANs, to assess the effect of allogeneic cord blood RBC transfusions (CB-RBCs) on severe ROP development. Recruitment, consent, and randomization take place at 10 neonatology intensive care units (NICUs) of 8 Italian tertiary hospitals. ELGANs with gestational age at birth comprised between 24+0 and 27+6 weeks are randomly allocated into two groups: (1) standard RBC transfusions (adult-RBCs) (control arm) and (2) CB-RBCs (intervention arm). In case of transfusion need, enrolled patients receive transfusions according to the allocation arm, unless an ABO/RhD CB-RBC is unavailable. Nine Italian public CB banks cooperate to make available a suitable amount of CB-RBC units for all participating NICUs. The primary outcome is the incidence of severe ROP (stage 3 or higher) at discharge or 40 weeks of postmenstrual age, which occurs first. DISCUSSION: BORN is a groundbreaking trial, pioneering a new transfusion approach dedicated to ELGANs at high risk for severe ROP. In previous non-randomized trials, this transfusion approach was proven feasible and able to prevent the HbF decrease in patients requiring multiple transfusions. Should the BORN trial confirm the efficacy of CB-RBCs in reducing ROP severity, this transfusion strategy would become the preferential blood product to be used in severely preterm neonates. TRIAL REGISTRATION: ClinicalTrials.gov NCT05100212. Registered on October 29, 2021.

A Computational Framework for Comprehensive Genomic Profiling in Solid Cancers: The Analytical Performance of a High-Throughput Assay for Small and Copy Number Variants.

In January 2022, our institution launched a comprehensive cancer genome profiling program on 10 cancer types using a non-IVD solution named the TruSight Oncology 500 Assay provided by Illumina®. The assay analyzes both DNA and RNA, identifying Single-Nucleotide Variants (SNV)s and Insertion-Deletion (InDel) in 523 genes, as well as known and unknown fusions and splicing variants in 55 genes and Copy Number Alterations (CNVs), Mutational Tumor Burden (MTB) and Microsatellite Instability (MSI). According to the current European IVD Directive 98/79/EC, an internal validation was performed before running the test. A dedicated open-source bioinformatics pipeline was developed for data postprocessing, panel assessment and embedding in high-performance computing framework using the container technology to ensure scalability and reproducibility. Our protocols, applied to 71 DNA and 64 RNA samples, showed full agreement between the TruSight Oncology 500 assay and standard approaches, with only minor limitations, allowing to routinely perform our protocol in patient screening.

Integrating a Comprehensive Cancer Genome Profiling into Clinical Practice: A Blueprint in an Italian Referral Center.

The implementation of cancer molecular characterization in clinical practice has improved prognostic re-definition, extending the eligibility to a continuously increasing number of targeted treatments. Broad molecular profiling technologies better than organ-based approaches are believed to serve such dynamic purposes. We here present the workflow our institution adopted to run a comprehensive cancer genome profiling in clinical practice. This article describes the workflow designed to make a comprehensive cancer genome profiling program feasible and sustainable in a large-volume referral hospital.

Bioinformatics: From NGS Data to Biological Complexity in Variant Detection and Oncological Clinical Practice.

The use of next-generation sequencing (NGS) techniques for variant detection has become increasingly important in clinical research and in clinical practice in oncology. Many cancer patients are currently being treated in clinical practice or in clinical trials with drugs directed against specific genomic alterations. In this scenario, the development of reliable and reproducible bioinformatics tools is essential to derive information on the molecular characteristics of each patient's tumor from the NGS data. The development of bioinformatics pipelines based on the use of machine learning and statistical methods is even more relevant for the determination of complex biomarkers. In this review, we describe some important technologies, computational algorithms and models that can be applied to NGS data from Whole Genome to Targeted Sequencing, to address the problem of finding complex cancer-associated biomarkers. In addition, we explore the future perspectives and challenges faced by bioinformatics for precision medicine both at a molecular and clinical level, with a focus on an emerging complex biomarker such as homologous recombination deficiency (HRD).

Identification of a novel gene signature predicting response to first-line chemotherapy in BRCA wild-type high-grade serous ovarian cancer patients.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) has poor survival rates due to a combination of diagnosis at advanced stage and disease recurrence as a result of chemotherapy resistance. In BRCA1 (Breast Cancer gene 1) - or BRCA2-wild type (BRCAwt) HGSOC patients, resistance and progressive disease occur earlier and more often than in mutated BRCA. Identification of biomarkers helpful in predicting response to first-line chemotherapy is a challenge to improve BRCAwt HGSOC management. METHODS: To identify a gene signature that can predict response to first-line chemotherapy, pre-treatment tumor biopsies from a restricted cohort of BRCAwt HGSOC patients were profiled by RNA sequencing (RNA-Seq) technology. Patients were sub-grouped according to platinum-free interval (PFI), into sensitive (PFI > 12 months) and resistant (PFI < 6 months). The gene panel identified by RNA-seq analysis was then tested by high-throughput quantitative real-time PCR (HT RT-qPCR) in a validation cohort, and statistical/bioinformatic methods were used to identify eligible markers and to explore the relevant pathway/gene network enrichments of the identified gene set. Finally, a panel of primary HGSOC cell lines was exploited to uncover cell-autonomous mechanisms of resistance. RESULTS: RNA-seq identified a 42-gene panel discriminating sensitive and resistant BRCAwt HGSOC patients and pathway analysis pointed to the immune system as a possible driver of chemotherapy response. From the extended cohort analysis of the 42 DEGs (differentially expressed genes), a statistical approach combined with the random forest classifier model generated a ten-gene signature predictive of response to first-line chemotherapy. The ten-gene signature included: CKB (Creatine kinase B), CTNNBL1 (Catenin, beta like 1), GNG11 (G protein subunit gamma 11), IGFBP7 (Insulin-like growth factor-binding protein 7), PLCG2 (Phospholipase C, gamma 2), RNF24 (Ring finger protein 24), SLC15A3 (Solute carrier family 15 member 3), TSPAN31 (Tetraspanin 31), TTI1 (TELO2 interacting protein 1) and UQCC1 (Ubiquinol-cytochrome c reductase complex assembly factor). Cytotoxicity assays, combined with gene-expression analysis in primary HGSOC cell lines, allowed to define CTNNBL1, RNF24, and TTI1 as cell-autonomous contributors to tumor resistance. CONCLUSIONS: Using machine-learning techniques we have identified a gene signature that could predict response to first-line chemotherapy in BRCAwt HGSOC patients, providing a useful tool towards personalized treatment modalities.

The impact of the COVID-19 pandemic on oncological disease extent at FDG PET/CT staging: the ONCOVIPET study.

PURPOSE: To investigate whether the COVID-19 pandemic and national lockdown had an impact on the extent of cancer disease at FDG PET/CT staging as surrogate marker. METHODS: Retrospective observational study including cancer patients submitted to FDG PET/CT staging from June 1 to October 31, 2020, and June 1 to October 31, 2019, respectively. Data regarding primary tumour, nodal (N) status and number of involved nodal stations, and presence and number of distant metastases (M) were collected. Each scan was classified in limited vs advanced status. Data were aggregated across the study population and tumour type. Bi-weekly frequencies of the observed events were analysed. RESULTS: Six hundred eleven patients were included (240 in 2019 vs 371 in 2020, respectively). A significant increase of advanced disease patients (rate 1.56, P < 0.001), N + or M + patients (rate 1.84 and 2.09, respectively, P < 0.001), and patients with a greater number of involved N stations or M (rate 2.01 and 2.06, respectively, P < 0.001) were found in 2020 compared with data of 2019. Analysis by tumour type showed a significant increase of advanced disease in lymphoma and lung cancer in 2020 compared with 2019 (P < 0.001). In addition, a significant increase of nodal involvement was found in lung, gastro-intestinal, and breast cancers, as well as in lymphoma patients (P < 0.02). A significant increase of distant metastases was found in lung cancers (P = 0.002). CONCLUSION: Cancer patients with advanced disease at FDG PET/CT staging increased in 2020 compared with 2019, following the national lockdown due to the COVID-19 pandemic, 1.5-fold with a significant increase of patients with N or M involvement. Targeted health interventions are needed to mitigate the effects of the pandemic on patient outcome.

The Vulvar Immunohistochemical Panel (VIP) Project: Molecular Profiles of Vulvar Squamous Cell Carcinoma.

INTRODUCTION: The study's aim was to investigate the immunohistochemical (IHC) expression of biological markers as potential prognostic/therapeutic factors in vulvar squamous cell carcinoma (VSCC). METHODOLOGY: A series of 101 patients surgically treated at our center from 2016 to 2020 were retrospectively enrolled: 53 node-negative (Group A) and 48 node-positive (Group B). A total of 146 samples, 101 from primary tumor (T) and 45 from nodal metastases (N), were investigated. The IHC panel included: p16, p53, MLH1, MSH2, MSH6, PMS2, PD-L1, CD3, HER2/neu, ER, PR, EGFR, VEGF, and CD31. The reactions were evaluated on qualitative and semi-quantitative scales. Generalized Linear Model (GLM) and cluster analysis were performed in R statistical environment. A distance plot compared the IHC panel of T with the correspondent N. RESULTS: In Group A: p16-positive expression (surrogate of HPV-dependent pathway) was significantly higher (20.8% vs. 6.2%, p = 0.04). In Group B: PD-L1 positivity and high EGFR expression were found, respectively, in 77.1% and 97.9% patients (T and/or N). Overall, p16-negative tumors showed a higher PD-L1 expression (60.9% vs. 50.0%). In both groups: tumoral immune infiltration (CD3 expression) was mainly moderate/intense (80% vs. 95%); VEGF showed strong/moderate-diffuse expression in 13.9% of T samples; CD31, related to tumoral microvessel density (MVD), showed no difference between groups; a mutated p53 and over-expressed PD-L1 showed significant association with nodal metastasis, with Odds Ratios (OR) of 4.26 (CI 95% = 1.14-15.87, p = 0.03) and 2.68 (CI 95% = 1.0-7.19, p < 0.05), respectively; since all mismatch repair proteins (MMR) showed a retained expression and ER, PR, and HER2/neu were negative, they were excluded from further analysis. The cluster analysis identified three and four sub-groups of molecular profiles, respectively, in Group A and B, with no difference in prognosis. The molecular signature of each N and corresponding T diverged significantly in 18/41 (43.9%) cases. CONCLUSIONS: Our results support a potential role of immune checkpoint inhibitors and anti-VEGF and anti-EGFR drugs especially in patients with worse prognosis (metastatic, HPV-independent). A panel including EGFR, VEGF, PDL1, p16, and p53 might be performed routinely in primary tumor and repeated in case of lymph node metastases to identify changes in marker expression.

Release of paused RNA polymerase II at specific loci favors DNA double-strand-break formation and promotes cancer translocations.

It is not clear how spontaneous DNA double-strand breaks (DSBs) form and are processed in normal cells, and whether they predispose to cancer-associated translocations. We show that DSBs in normal mammary cells form upon release of paused RNA polymerase II (Pol II) at promoters, 5' splice sites and active enhancers, and are processed by end-joining in the absence of a canonical DNA-damage response. Logistic and causal-association models showed that Pol II pausing at long genes is the main predictor and determinant of DSBs. Damaged introns with paused Pol II-pS5, TOP2B and XRCC4 are enriched in translocation breakpoints, and map at topologically associating domain boundary-flanking regions showing high interaction frequencies with distal loci. Thus, in unperturbed growth conditions, release of paused Pol II at specific loci and chromatin territories favors DSB formation, leading to chromosomal translocations.

Integrating Rio1 activities discloses its nutrient-activated network in Saccharomyces cerevisiae.

The Saccharomyces cerevisiae kinase/adenosine triphosphatase Rio1 regulates rDNA transcription and segregation, pre-rRNA processing and small ribosomal subunit maturation. Other roles are unknown. When overexpressed, human ortholog RIOK1 drives tumor growth and metastasis. Likewise, RIOK1 promotes 40S ribosomal subunit biogenesis and has not been characterized globally. We show that Rio1 manages directly and via a series of regulators, an essential signaling network at the protein, chromatin and RNA levels. Rio1 orchestrates growth and division depending on resource availability, in parallel to the nutrient-activated Tor1 kinase. To define the Rio1 network, we identified its physical interactors, profiled its target genes/transcripts, mapped its chromatin-binding sites and integrated our data with yeast's protein-protein and protein-DNA interaction catalogs using network computation. We experimentally confirmed network components and localized Rio1 also to mitochondria and vacuoles. Via its network, Rio1 commands protein synthesis (ribosomal gene expression, assembly and activity) and turnover (26S proteasome expression), and impinges on metabolic, energy-production and cell-cycle programs. We find that Rio1 activity is conserved to humans and propose that pathological RIOK1 may fuel promiscuous transcription, ribosome production, chromosomal instability, unrestrained metabolism and proliferation; established contributors to cancer. Our study will advance the understanding of numerous processes, here revealed to depend on Rio1 activity.

In Vivo Genetic Screens of Patient-Derived Tumors Revealed Unexpected Frailty of the Transformed Phenotype.

UNLABELLED: The identification of genes maintaining cancer growth is critical to our understanding of tumorigenesis. We report the first in vivo genetic screen of patient-derived tumors, using metastatic melanomas and targeting 236 chromatin genes by expression of specific shRNA libraries. Our screens revealed unprecedented numerosity of genes indispensable for tumor growth (∼50% of tested genes) and unexpected functional heterogeneity among patients (<15% in common). Notably, these genes were not activated by somatic mutations in the same patients and are therefore distinguished from mutated cancer driver genes. We analyzed underlying molecular mechanisms of one of the identified genes, the Histone-lysine N-methyltransferase KMT2D, and showed that it promotes tumorigenesis by dysregulating a subset of transcriptional enhancers and target genes involved in cell migration. The assembly of enhancer genomic patterns by activated KMT2D was highly patient-specific, regardless of the identity of transcriptional targets, suggesting that KMT2D might be activated by distinct upstream signaling pathways. SIGNIFICANCE: Drug targeting of biologically relevant cancer-associated mutations is considered a critical strategy to control cancer growth. Our functional in vivo genetic screens of patient-derived tumors showed unprecedented numerosity and interpatient heterogeneity of genes that are essential for tumor growth, but not mutated, suggesting that multiple, patient-specific signaling pathways are activated in tumors. Cancer Discov; 6(6); 650-63. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 561.

The hidden genomic landscape of acute myeloid leukemia: subclonal structure revealed by undetected mutations.

The analyses carried out using 2 different bioinformatics pipelines (SomaticSniper and MuTect) on the same set of genomic data from 133 acute myeloid leukemia (AML) patients, sequenced inside the Cancer Genome Atlas project, gave discrepant results. We subsequently tested these 2 variant-calling pipelines on 20 leukemia samples from our series (19 primary AMLs and 1 secondary AML). By validating many of the predicted somatic variants (variant allele frequencies ranging from 100% to 5%), we observed significantly different calling efficiencies. In particular, despite relatively high specificity, sensitivity was poor in both pipelines resulting in a high rate of false negatives. Our findings raise the possibility that landscapes of AML genomes might be more complex than previously reported and characterized by the presence of hundreds of genes mutated at low variant allele frequency, suggesting that the application of genome sequencing to the clinic requires a careful and critical evaluation. We think that improvements in technology and workflow standardization, through the generation of clear experimental and bioinformatics guidelines, are fundamental to translate the use of next-generation sequencing from research to the clinic and to transform genomic information into better diagnosis and outcomes for the patient.

B-Pred, a structure based B-cell epitopes prediction server.

The ability to predict immunogenic regions in selected proteins by in-silico methods has broad implications, such as allowing a quick selection of potential reagents to be used as diagnostics, vaccines, immunotherapeutics, or research tools in several branches of biological and biotechnological research. However, the prediction of antibody target sites in proteins using computational methodologies has proven to be a highly challenging task, which is likely due to the somewhat elusive nature of B-cell epitopes. This paper proposes a web-based platform for scoring potential immunological reagents based on the structures or 3D models of the proteins of interest. The method scores a protein's peptides set, which is derived from a sliding window, based on the average solvent exposure, with a filter on the average local model quality for each peptide. The platform was validated on a custom-assembled database of 1336 experimentally determined epitopes from 106 proteins for which a reliable 3D model could be obtained through standard modeling techniques. Despite showing poor sensitivity, this method can achieve a specificity of 0.70 and a positive predictive value of 0.29 by combining these two simple parameters. These values are slightly higher than those obtained with other established sequence-based or structure-based methods that have been evaluated using the same epitopes dataset. This method is implemented in a web server called B-Pred, which is accessible at http://immuno.bio.uniroma2.it/bpred. The server contains a number of original features that allow users to perform personalized reagent searches by manipulating the sliding window's width and sliding step, changing the exposure and model quality thresholds, and running sequential queries with different parameters. The B-Pred server should assist experimentalists in the rational selection of epitope antigens for a wide range of applications.

A new Mycobacterium tuberculosis smooth colony reduces growth inside human macrophages and represses PDIM Operon gene expression. Does an heterogeneous population exist in intracellular mycobacteria?

Mycobacterium tuberculosis (MTB) colony morphology was associated to the pathogen's virulence. We isolated a new MTB H37Rv smooth colony, which only appeared following human macrophages (MDM) infection. The new phenotype was Alcohol-Acid resistant, but devoid of a covering capsule and biofilm defective. We ascertained that there were no deletions in the Rv0096-Rv0101 PDIM Operon, but that its expression was repressed as compared to MTB wild type (wt). Its lipid composition displayed lower PDIM components and higher TAG as compared to wt. In MDM it induced the sigma factors sigB, sigI and sigL expression vs. synthetic medium culture, while it repressed other six sigma factors. It also induced, significantly more than wt, mprA, a mycobacterial persistence regulator. It was phagocytosed more than wt by MDM, where it grew significantly less, but persisted therein till 14 days infection. It induced significantly less IFN-γ, IL-12 and IL-27 transcription than wt in infected MDM, while it increased the transcription of inducible NOS. It resided in mature, LAMP-3 positive phagolysosomes, where it never formed cords. This apparently "weaker" colony might represent an adaptive intracellular phenotype, whose infection may be less productive, but probably better equipped for a long lasting persistence in mildly activated host cells.