The leaf idioblastome of the medicinal plant Catharanthus roseus is associated with stress resistance and alkaloid metabolism

Catharanthus roseus leaves produce a range of monoterpenoid indole alkaloids (MIAs) that include low levels of the anticancer drugs vinblastine and vincristine. The MIA pathway displays a complex architecture spanning different subcellular and cell type localizations, and is under complex regulation. As a result, the development of strategies to increase the levels of the anticancer MIAs has remained elusive. The pathway involves mesophyll specialized idioblasts where the late unsolved biosynthetic steps are thought to occur. Here, protoplasts of C. roseus leaf idioblasts were isolated by fluorescence-activated cell sorting, and their differential alkaloid and transcriptomic profiles were characterized. This involved the assembly of an improved C. roseus transcriptome from short- and long-read data, IDIO+. It was observed that C. roseus mesophyll idioblasts possess a distinctive transcriptomic profile associated with protection against biotic and abiotic stresses, and indicative that this cell type is a carbon sink, in contrast to surrounding mesophyll cells. Moreover, it is shown that idioblasts are a hotspot of alkaloid accumulation, suggesting that their transcriptome may hold the key to the in-depth understanding of the MIA pathway and the success of strategies leading to higher levels of the anticancer drugs.

Abstract 1276: Nucleolin has prognostic value in neuroblastoma patients

Background: Neuroblastoma (NB) represents the most frequent form of extracranial solid tumor of infants, responsible for 15% of childhood cancer deaths. Nucleolin (NCL) prognostic value in NB was here investigated.

Methods: NCL protein expression was evaluated in NB patients at diagnosis and after induction chemotherapy. NCL mRNA prognostic value was first assessed in a cohort of 20 stage M NB patients and confirmed in the MultiPlatform786 including 786 NB patients of all stages. Overall and event-free survival curves were plotted by Kaplan-Meier method and compared by log-rank test.

Findings: NCL protein resulted significantly overexpressed in NB tumors compared to the non tumoral counterpart, and higher in stage M compared to stage L patients. In the stage M cohort and in MultiPlatform786 dataset, patients with high NCL mRNA expression revealed a significant lower survival probability than those with low NCL expression. In MultiPlatform786 dataset, NCL mRNA expression was significantly higher in patients with age >18 months, in stage M and in MYCN amplified tumors than in patients with age ˂18 months and in stage L or MS and with MYCN non amplified tumors, respectively. Multivariate analysis suggested NCL has a significant prognostic value even in the model adjusted for established prognostic markers. NCL significantly stratified patients with age <18 and age >18, stage M, >18 months and stage M tumor, stages L or MS, and with MYCN not amplified. A significant correlation between NCL and MYCN, MYC, and TERT was found in two independent datasets. Gene set enrichment analysis revealed a significant positive enrichment of MYC target genes and genes involved in telomerase maintenance. NCL protein resulted down-modulated after chemotherapy, in association with morphological features of neuroblastic differentiation.

Interpretation: NCL is a novel and independent prognostic marker for NB.

Funding: IMH-EuroNanoMed II-2015 (ER-2015-2360441-Eranet) and AIRC IG n. 24397 to PF.

Citation Format: Davide Cangelosi, Chiara Brignole, Veronica Bensa, Roberto Tamma, Fabiana Malaguti, Barbara Carlini, Enzo Calarco, Patrizia Perri, Domenico Ribatti, Nuno A. Fonseca, Joao N. Moreira, Alessandra Eva, Loredana Amoroso, Massimo Conte, Alberto Garaventa, Angela R. Sementa, Maria V. Corrias, Mirco Ponzoni, Fabio Pastorino. Nucleolin has prognostic value in neuroblastoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1276.

Speeding up the detection of invasive bivalve species using environmental DNA: a Nanopore and Illumina sequencing comparison

Traditional detection of aquatic invasive species via morphological identification is often time-consuming and can require a high level of taxonomic expertise, leading to delayed mitigation responses. Environmental DNA (eDNA) detection approaches of multiple species using Illumina-based sequencing technology have been used to overcome these hindrances, but sample processing is often lengthy. More recently, portable nanopore sequencing technology has become available, which has the potential to make molecular detection of invasive species more widely accessible and substantially decrease sample turnaround times. However, nanopore-sequenced reads have a much higher error rate than those produced by Illumina platforms, which has so far hindered the adoption of this technology. We provide a detailed laboratory protocol and bioinformatic tools (msi package) to increase the reliability of nanopore sequencing to detect invasive species, and we test its application using invasive bivalves while comparing it with Illumina-based sequencing. We sampled water from sites with pre-existing bivalve occurrence and abundance data, and contrasting bivalve communities, in Italy and Portugal. Samples were extracted, amplified, and sequenced by the two platforms. The mean agreement between sequencing methods was 69% and the difference between methods was non-significant. The lack of detections of some species at some sites could be explained by their known low abundances. This is the first reported use of MinION to detect aquatic invasive species from eDNA samples.

Modelling the impact of nucleolin expression level on the activity of F3 peptide-targeted pH-sensitive pegylated liposomes containing doxorubicin

Strategies targeting nucleolin have enabled a significant improvement in intracellular bioavailability of their encapsulated payloads. In this respect, assessment of the impact of target cell heterogeneity and nucleolin homology across species (structurally and functionally) is of major importance. This work also aimed at mathematically modelling the nucleolin expression levels at the cell membrane, binding and internalization of pH-sensitive pegylated liposomes encapsulating doxorubicin and functionalized with the nucleolin-binding F3 peptide (PEGASEMP), and resulting cytotoxicity against cancer cells from mouse, rat, canine, and human origin. Herein, it was shown that nucleolin expression levels were not a limitation on the continuous internalization of F3 peptide-targeted liposomes, despite the saturable nature of the binding mechanism. Modeling enabled the prediction of nucleolin-mediated total doxorubicin exposure provided by the experimental settings of the assessment of PEGASEMP's impact on cell death. The former increased proportionally with nucleolin-binding sites, a measure relevant for patient stratification. This pattern of variation was observed for the resulting cell death in nonsaturating conditions, depending on the cancer cell sensitivity to doxorubicin. This approach differs from standard determination of cytotoxic concentrations, which normally report values of incubation doses rather than the actual intracellular bioactive drug exposure. Importantly, in the context of development of nucleolin-based targeted drug delivery, the structural nucleolin homology (higher than 84%) and functional similarity across species presented herein, emphasized the potential to use toxicological data and other metrics from lower species to infer the dose for a first-in-human trial.

The Enhanced Efficacy of Intracellular Delivery of Doxorubicin/C6-Ceramide Combination Mediated by the F3 Peptide/Nucleolin System Is Supported by the Downregulation of the PI3K/Akt Pathway

Simple Summary

Targeted nanomedicine-based approaches that aim at the simultaneous delivery of synergistic drug combinations to multiple cellular populations are of high relevance for tackling heterogeneity on solid tumors. Considering that cancer stem cells (CSC) may originate from non-stem cancer cells, single-drug regimens targeting only one of these cell populations could enable tumors to evade treatments. As such, the identification of a common marker, such as nucleolin, might result in a therapeutic advantage. The results herein generated suggested a transversal role of nucleolin in the internalization of F3 peptide-targeted pegylated pH-sensitive liposomes into bulk ovarian cancer cells, including putative CSC-enriched ovarian cells. The intracellular delivery of a drug combination such as the one tested herein was relevant in the context of cell lines with higher intrinsic resistances to doxorubicin. The enhanced efficacy of the F3 peptide-targeted liposomal combination of doxorubicin/C6-ceramide was supported by the downregulation of the Akt pathway, within a specific range of basal level of expression.

Abstract

Targeting multiple cellular populations is of high therapeutic relevance for the tackling of solid tumors heterogeneity. Herein, the ability of pegylated and pH-sensitive liposomes, functionalized with the nucleolin-binding F3 peptide and containing doxorubicin (DXR)/C6-ceramide synergistic combination, to target, in vitro, ovarian cancer, including ovarian cancer stem cells (CSC), was assessed. The underlying molecular mechanism of action of the nucleolin-mediated intracellular delivery of C6-ceramide to cancer cells was also explored. The assessment of overexpression of surface nucleolin expression by flow cytometry was critical to dissipate differences identified by Western blot in membrane/cytoplasm of SKOV-3, OVCAR-3 and TOV-112D ovarian cancer cell lines. The former was in line with the significant extent of uptake into (bulk) ovarian cancer cells, relative to non-targeted and non-specific counterparts. This pattern of uptake was recapitulated with putative CSC-enriched ovarian SKOV-3 and OVCAR-3 sub-population (EpCAM^high/CD44^high). Co-encapsulation of DXR:C6-ceramide into F3 peptide-targeted liposomes improved cytotoxic activity relative to liposomes containing DXR alone, in an extent that depended on the intrinsic resistance to DXR and on the incubation time. The enhanced cytotoxicity of the targeted combination was mechanistically supported by the downregulation of PI3K/Akt pathway by C6-ceramide, only among the nucleolin-overexpressing cancer cells presenting a basal p-Akt/total Akt ratio lower than 1.

Cell surface Nucleolin represents a novel cellular target for neuroblastoma therapy

BACKGROUND

Neuroblastoma (NB) represents the most frequent and aggressive form of extracranial solid tumor of infants. Nucleolin (NCL) is a protein overexpressed and partially localized on the cell surface of tumor cells of adult cancers. Little is known about NCL and pediatric tumors and nothing is reported about cell surface NCL and NB.

METHODS

NB cell lines, Schwannian stroma-poor NB tumors and bone marrow (BM)-infiltrating NB cells were evaluated for the expression of cell surface NCL by Flow Cytometry, Imaging Flow Cytometry and Immunohistochemistry analyses. The cytotoxic activity of doxorubicin (DXR)-loaded nanocarriers decorated with the NCL-recognizing F3 peptide (T-DXR) was evaluated in terms of inhibition of NB cell proliferation and induction of cell death in vitro, whereas metastatic and orthotopic animal models of NB were used to examine their in vivo anti-tumor potential.

RESULTS

NB cell lines, NB tumor cells (including patient-derived and Patient-Derived Xenografts-PDX) and 70% of BM-infiltrating NB cells show cell surface NCL expression. NCL staining was evident on both tumor and endothelial tumor cells in NB xenografts. F3 peptide-targeted nanoparticles, co-localizing with cell surface NCL, strongly associates with NB cells showing selective tumor cell internalization. T-DXR result significantly more effective, in terms of inhibition of cell proliferation and reduction of cell viability in vitro, and in terms of delay of tumor growth in all NB animal model tested, when compared to both control mice and those treated with the untargeted formulation.

CONCLUSIONS

Our findings demonstrate that NCL could represent an innovative therapeutic cellular target for NB.

Comparative Genomics of Xanthomonas euroxanthea and Xanthomonas arboricola pv. juglandis Strains Isolated from a Single Walnut Host Tree

The recent report of distinct Xanthomonas lineages of Xanthomonas arboricola pv. juglandis and Xanthomonas euroxanthea within the same walnut tree revealed that this consortium of walnut-associated Xanthomonas includes both pathogenic and nonpathogenic strains. As the implications of this co-colonization are still poorly understood, in order to unveil niche-specific adaptations, the genomes of three X. euroxanthea strains (CPBF 367, CPBF 424^T, and CPBF 426) and of an X. arboricola pv. juglandis strain (CPBF 427) isolated from a single walnut tree in Loures (Portugal) were sequenced with two different technologies, Illumina and Nanopore, to provide consistent single scaffold chromosomal sequences. General genomic features showed that CPBF 427 has a genome similar to other X. arboricola pv. juglandis strains, regarding its size, number, and content of CDSs, while X. euroxanthea strains show a reduction regarding these features comparatively to X. arboricola pv. juglandis strains. Whole genome comparisons revealed remarkable genomic differences between X. arboricola pv. juglandis and X. euroxanthea strains, which translates into different pathogenicity and virulence features, namely regarding type 3 secretion system and its effectors and other secretory systems, chemotaxis-related proteins, and extracellular enzymes. Altogether, the distinct genomic repertoire of X. euroxanthea may be particularly useful to address pathogenicity emergence and evolution in walnut-associated Xanthomonas.

Tumour gene expression signature in primary melanoma predicts long-term outcomes

Adjuvant systemic therapies are now routinely used following resection of stage III melanoma, however accurate prognostic information is needed to better stratify patients. We use differential expression analyses of primary tumours from 204 RNA-sequenced melanomas within a large adjuvant trial, identifying a 121 metastasis-associated gene signature. This signature strongly associated with progression-free (HR = 1.63, p = 5.24 × 10-5) and overall survival (HR = 1.61, p = 1.67 × 10-4), was validated in 175 regional lymph nodes metastasis as well as two externally ascertained datasets. The machine learning classification models trained using the signature genes performed significantly better in predicting metastases than models trained with clinical covariates (pAUROC = 7.03 × 10-4), or published prognostic signatures (pAUROC < 0.05). The signature score negatively correlated with measures of immune cell infiltration (ρ = -0.75, p < 2.2 × 10-16), with a higher score representing reduced lymphocyte infiltration and a higher 5-year risk of death in stage II melanoma. Our expression signature identifies melanoma patients at higher risk of metastases and warrants further evaluation in adjuvant clinical trials.

In Vitro and In Vivo Tumor Models for the Evaluation of Anticancer Nanoparticles

Multiple studies about tumor biology have revealed the determinant role of the tumor microenvironment in cancer progression, resulting from the dynamic interactions between tumor cells and surrounding stromal cells within the extracellular matrix. This malignant microenvironment highly impacts the efficacy of anticancer nanoparticles by displaying drug resistance mechanisms, as well as intrinsic physical and biochemical barriers, which hamper their intratumoral accumulation and biological activity.Currently, two-dimensional cell cultures are used as the initial screening method in vitro for testing cytotoxic nanocarriers. However, this fails to mimic the tumor heterogeneity, as well as the three-dimensional tumor architecture and pathophysiological barriers, leading to an inaccurate pharmacological evaluation.Biomimetic 3D in vitro tumor models, on the other hand, are emerging as promising tools for more accurately assessing nanoparticle activity, owing to their ability to recapitulate certain features of the tumor microenvironment and thus provide mechanistic insights into nanocarrier intratumoral penetration and diffusion rates.Notwithstanding, in vivo validation of nanomedicines remains irreplaceable at the preclinical stage, and a vast variety of more advanced in vivo tumor models is currently available. Such complex animal models (e.g., genetically engineered mice and patient-derived xenografts) are capable of better predicting nanocarrier clinical efficiency, as they closely resemble the heterogeneity of the human tumor microenvironment.Herein, the development of physiologically more relevant in vitro and in vivo tumor models for the preclinical evaluation of anticancer nanoparticles will be discussed, as well as the current limitations and future challenges in clinical translation.

Abstract LB-274: Primary tumor gene expression signature predicts long-term outcomes in primary melanoma: A prospective multicenter study

Purpose: Adjuvant therapies prolong survival in patients with stage III melanoma. However, biomarkers are needed to stratify patients with primary melanoma at highest risk for metastases which could help minimize exposure to potentially irreversible toxicities and allow for rational clinical trial designs in the adjuvant setting.

Methods: We analyzed data from 194 RNA-sequenced primary cutaneous melanomas from patients with stage IIB-IIIC disease recruited to the multicenter AVAST-M phase III randomized trial. By undertaking covariate-corrected differential expression between patients experiencing distant metastasis (n=89) versus no-metastases (n=105), we identified metastasis-associated genes of which 121 were externally validated and made up our predictive signature, “Cam_121”. Several machine learning classification models were trained using nested leave-one-out cross validation (LOOCV) to test the signature's capacity to predict metastases. Univariate and multivariate Cox proportional hazard regression survival analyses were performed. The signatures' predictive accuracy was further externally validated in an independent population-controlled cohort study measuring melanoma-specific survival (Leeds Melanoma Cohort, n=687).

Results: The signature distinguished patients with distant recurrence from those without across multiple machine learning models (sensitivity=0.64, specificity=0.79, accuracy=0.72, kappa=0.43) and performed significantly better than any of the models trained with the clinical covariates alone (pAccuracy =4.92x10-3), as well as those trained with predictive signatures selected from two published datasets (Decision-Dx MelanomaTM and Leeds Melanoma Cohort 150 genes). The signature also correlated with progression-free survival (PFS), overall survival (OS) and melanoma-specific survival (MSS) while retaining its predictive accuracy following multivariate correction (PFS: HR=0.49 (0.35-0.69), p=2.8x10-5, OS: HR=0.6 (0.42-0.86), p=0.005 and MSS: HR=0.57, p=8x10-5). Importantly, we found that the median signature expression score positively correlated with measures of immune cell infiltration, with a lower score representing a poorer tumor lymphocytic infiltration and worse long-term prognosis.

Conclusions: We have identified Cam_121 a primary melanoma expression signature that outperforms currently available predictive signatures. The signature confirms (using unbiased approaches) the central prognostic importance of immune cell infiltration in long-term patient outcomes and could help identify primary melanoma patients at highest risk of metastases and poor survival who might benefit most from adjuvant therapies.

Citation Format: Manik Garg, Dominique-Laurent Courturier, Nuno A. Fonseca, Matthew Wongchenko, Yibing Yan, Jeremie Nsengimana, Tim Bishop, Julia Newton-Bishop, Mark Middleton, Pippa Corrie, David J. Adams, Alvis Brazma, Roy Rabbie. Primary tumor gene expression signature predicts long-term outcomes in primary melanoma: A prospective multicenter study [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-274.

Gastric Microbiome Diversities in Gastric Cancer Patients from Europe and Asia Mimic the Human Population Structure and Are Partly Driven by Microbiome Quantitative Trait Loci

The human gastrointestinal tract harbors approximately 100 trillion microorganisms with different microbial compositions across geographic locations. In this work, we used RNASeq data from stomach samples of non-disease (164 individuals from European ancestry) and gastric cancer patients (137 from Europe and Asia) from public databases. Although these data were intended to characterize the human expression profiles, they allowed for a reliable inference of the microbiome composition, as confirmed from measures such as the genus coverage, richness and evenness. The microbiome diversity (weighted UniFrac distances) in gastric cancer mimics host diversity across the world, with European gastric microbiome profiles clustering together, distinct from Asian ones. Despite the confirmed loss of microbiome diversity from a healthy status to a cancer status, the structured profile was still recognized in the disease condition. In concordance with the parallel host-bacteria population structure, we found 16 human loci (non-synonymous variants) in the European-descendent cohorts that were significantly associated with specific genera abundance. These microbiome quantitative trait loci display heterogeneity between population groups, being mainly linked to the immune system or cellular features that may play a role in enabling microbe colonization and inflammation.

Tumors induce de novo steroid biosynthesis in T cells to evade immunity

Tumors subvert immune cell function to evade immune responses, yet the complex mechanisms driving immune evasion remain poorly understood. Here we show that tumors induce de novo steroidogenesis in T lymphocytes to evade anti-tumor immunity. Using a transgenic steroidogenesis-reporter mouse line we identify and characterize de novo steroidogenic immune cells, defining the global gene expression identity of these steroid-producing immune cells and gene regulatory networks by using single-cell transcriptomics. Genetic ablation of T cell steroidogenesis restricts primary tumor growth and metastatic dissemination in mouse models. Steroidogenic T cells dysregulate anti-tumor immunity, and inhibition of the steroidogenesis pathway is sufficient to restore anti-tumor immunity. This study demonstrates T cell de novo steroidogenesis as a mechanism of anti-tumor immunosuppression and a potential druggable target.

An RNA-seq Based Machine Learning Approach Identifies Latent Tuberculosis Patients With an Active Tuberculosis Profile

A better understanding of the response against Tuberculosis (TB) infection is required to accurately identify the individuals with an active or a latent TB infection (LTBI) and also those LTBI patients at higher risk of developing active TB. In this work, we have used the information obtained from studying the gene expression profile of active TB patients and their infected –LTBI- or uninfected –NoTBI- contacts, recruited in Spain and Mozambique, to build a class-prediction model that identifies individuals with a TB infection profile. Following this approach, we have identified several genes and metabolic pathways that provide important information of the immune mechanisms triggered against TB infection. As a novelty of our work, a combination of this class-prediction model and the direct measurement of different immunological parameters, was used to identify a subset of LTBI contacts (called TB-like) whose transcriptional and immunological profiles are suggestive of infection with a higher probability of developing active TB. Validation of this novel approach to identifying LTBI individuals with the highest risk of active TB disease merits further longitudinal studies on larger cohorts in TB endemic areas.

The InBIO Barcoding Initiative Database: contribution to the knowledge on DNA barcodes of Iberian Plecoptera

BACKGROUND

The use of DNA barcoding allows unprecedented advances in biodiversity assessments and monitoring schemes of freshwater ecosystems; nevertheless, it requires the construction of comprehensive reference collections of DNA sequences that represent the existing biodiversity. Plecoptera are considered particularly good ecological indicators and one of the most endangered groups of insects, but very limited information on their DNA barcodes is available in public databases. Currently, less than 50% of the Iberian species are represented in BOLD.

NEW INFORMATION

The InBIO Barcoding Initiative Database: contribution to the knowledge on DNA barcodes of Iberian Plecoptera dataset contains records of 71 specimens of Plecoptera. All specimens have been morphologically identified to species level and belong to 29 species in total. This dataset contributes to the knowledge on the DNA barcodes and distribution of Plecoptera from the Iberian Peninsula and it is one of the IBI database public releases that makes available genetic and distribution data for a series of taxa.The species represented in this dataset correspond to an addition to public databases of 17 species and 21 BINs. Fifty-eight specimens were collected in Portugal and 18 in Spain during the period of 2004 to 2018. All specimens are deposited in the IBI collection at CIBIO, Research Center in Biodiversity and Genetic Resources and their DNA barcodes are publicly available in the Barcode of Life Data System (BOLD) online database. The distribution dataset can be freely accessed through the Global Biodiversity Information Facility (GBIF).

A Pan-cancer Transcriptome Analysis Reveals Pervasive Regulation through Alternative Promoters

Most human protein-coding genes are regulated by multiple, distinct promoters, suggesting that the choice of promoter is as important as its level of transcriptional activity. However, while a global change in transcription is recognized as a defining feature of cancer, the contribution of alternative promoters still remains largely unexplored. Here, we infer active promoters using RNA-seq data from 18,468 cancer and normal samples, demonstrating that alternative promoters are a major contributor to context-specific regulation of transcription. We find that promoters are deregulated across tissues, cancer types, and patients, affecting known cancer genes and novel candidates. For genes with independently regulated promoters, we demonstrate that promoter activity provides a more accurate predictor of patient survival than gene expression. Our study suggests that a dynamic landscape of active promoters shapes the cancer transcriptome, opening new diagnostic avenues and opportunities to further explore the interplay of regulatory mechanisms with transcriptional aberrations in cancer.

Expression Atlas update: from tissues to single cells

Expression Atlas is EMBL-EBI's resource for gene and protein expression. It sources and compiles data on the abundance and localisation of RNA and proteins in various biological systems and contexts and provides open access to this data for the research community. With the increased availability of single cell RNA-Seq datasets in the public archives, we have now extended Expression Atlas with a new added-value service to display gene expression in single cells. Single Cell Expression Atlas was launched in 2018 and currently includes 123 single cell RNA-Seq studies from 12 species. The website can be searched by genes within or across species to reveal experiments, tissues and cell types where this gene is expressed or under which conditions it is a marker gene. Within each study, cells can be visualized using a pre-calculated t-SNE plot and can be coloured by different features or by cell clusters based on gene expression. Within each experiment, there are links to downloadable files, such as RNA quantification matrices, clustering results, reports on protocols and associated metadata, such as assigned cell types.

ArrayExpress update - from bulk to single-cell expression data

ArrayExpress (https://www.ebi.ac.uk/arrayexpress) is an archive of functional genomics data from a variety of technologies assaying functional modalities of a genome, such as gene expression or promoter occupancy. The number of experiments based on sequencing technologies, in particular RNA-seq experiments, has been increasing over the last few years and submissions of sequencing data have overtaken microarray experiments in the last 12 months. Additionally, there is a significant increase in experiments investigating single cells, rather than bulk samples, known as single-cell RNA-seq. To accommodate these trends, we have substantially changed our submission tool Annotare which, along with raw and processed data, collects all metadata necessary to interpret these experiments. Selected datasets are re-processed and loaded into our sister resource, the value-added Expression Atlas (and its component Single Cell Expression Atlas), which not only enables users to interpret the data easily but also serves as a test for data quality. With an increasing number of studies that combine different assay modalities (multi-omics experiments), a new more general archival resource the BioStudies Database has been developed, which will eventually supersede ArrayExpress. Data submissions will continue unchanged; all existing ArrayExpress data will be incorporated into BioStudies and the existing accession numbers and application programming interfaces will be maintained.

The InBIO Barcoding Initiative Database: DNA barcodes of Portuguese Diptera 01

Background

The InBIO Barcoding Initiative (IBI) Diptera 01 dataset contains records of 203 specimens of Diptera. All specimens have been morphologically identified to species level, and belong to 154 species in total. The species represented in this dataset correspond to about 10% of continental Portugal dipteran species diversity. All specimens were collected north of the Tagus river in Portugal. Sampling took place from 2014 to 2018, and specimens are deposited in the IBI collection at CIBIO, Research Center in Biodiversity and Genetic Resources.

New information

This dataset contributes to the knowledge on the DNA barcodes and distribution of 154 species of Diptera from Portugal and is the first of the planned IBI database public releases, which will make available genetic and distribution data for a series of taxa. All specimens have their DNA barcodes made publicly available in the Barcode of Life Data System (BOLD) online database and the distribution dataset can be freely accessed through the Global Biodiversity Information Facility (GBIF).

High-coverage whole-genome analysis of 1220 cancers reveals hundreds of genes deregulated by rearrangement-mediated cis-regulatory alterations

The impact of somatic structural variants (SVs) on gene expression in cancer is largely unknown. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole-genome sequencing data and RNA sequencing from a common set of 1220 cancer cases, we report hundreds of genes for which the presence within 100 kb of an SV breakpoint associates with altered expression. For the majority of these genes, expression increases rather than decreases with corresponding breakpoint events. Up-regulated cancer-associated genes impacted by this phenomenon include TERT, MDM2, CDK4, ERBB2, CD274, PDCD1LG2, and IGF2. TERT-associated breakpoints involve ~3% of cases, most frequently in liver biliary, melanoma, sarcoma, stomach, and kidney cancers. SVs associated with up-regulation of PD1 and PDL1 genes involve ~1% of non-amplified cases. For many genes, SVs are significantly associated with increased numbers or greater proximity of enhancer regulatory elements near the gene. DNA methylation near the promoter is often increased with nearby SV breakpoint, which may involve inactivation of repressor elements.

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

Genomic basis for RNA alterations in cancer

Transcript alterations often result from somatic changes in cancer genomes1. Various forms of RNA alterations have been described in cancer, including overexpression2, altered splicing3 and gene fusions4; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)5. Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer.

Current challenges and emerging opportunities of CAR-T cell therapies

Infusion of chimeric antigen receptor (CAR)-genetically modified T cells (CAR-T cells) have led to remarkable clinical responses and cancer remission in patients suffering from relapsed or refractory B-cell malignancies. This is a new form of adoptive T cell therapy (ACT), whereby the artificial CAR enables the redirection of T cells endogenous antitumor activity towards a predefined tumor-associated antigen, leading to the elimination of a specific tumor. The early success in blood cancers has prompted the US Food and Drug Administration (FDA) to approve the first CAR-T cell therapies for the treatment of CD19-positive leukemias and lymphomas in 2017. Despite the emergence of CAR-T cells as one of the latest breakthroughs of cancer immunotherapies, their wider application has been hampered by specific life-threatening toxicities, and a substantial lack of efficacy in the treatment of solid tumors, owing to the strong immunosuppressive tumor microenvironment and the paucity of reliable tumor-specific targets. Herein, besides providing an overview of the emerging CAR-technologies and current clinical applications, the major hurdles of CAR-T cell therapies will be discussed, namely treatment-related life-threatening toxicities and the obstacles posed by the immunosupressive tumor-microenvironment of solid tumors, as well as the next-generation strategies currently designed to simultaneously improve safety and efficacy of CAR-T cell therapies in vivo.

Abstract 3622: Differential effect of liposomal C6-ceramide/doxorubicin targeted to nucleolin and conventional combinations against triple negative breast cancer stem cells

The interconversion between cancer stem cells (CSCs) and non-stem cancer cells (non-SCCs) in response to environmental stimulus, has urged the need to identify markers common to both cell sub-populations. This is the case of cell surface nucleolin, a target for drug delivery, offering the opportunity to target both cell populations as previously demonstrated (Fonseca, Biomaterials 2015). Herein, it is hypothesized that the intracellular delivery of the developed liposomal synergistic combination of doxorubicin (DXR) and the sphingolipid C6-ceramide (C6), functionalized with a nucleolin-binding peptide, [F3]L-DC6, will imbalance the CSC niche of triple-negative breast cancer (TNBC), relative to a clinically used combination of DXR and cisplatin (Cis). Cytotoxicity against (bulk) TNBC cell lines (MDA-MB-231, MDA-MB-468 and HS-578T) was assessed by the rezasurin assay. The impact over the putative CSCs population (ALDHhigh, as determined by the Aldefluor assay) was evaluated by flow cytometry. Moreover, assessment of the effect of each drug combination on the in vitro stemness properties of TNBC cells (the mRNA levels of pluripotency transcripts OCT4 and NANOG and mammosphere-forming capacity) was also performed. The intracellular delivery of the DXR:C6 (1:1 molar ratio) combination provided by the formulation targeted to nucleolin ([F3]L-DC6) enabled a significant increase in bulk cell death, compared with the counterpart single drug formulation. In fact, only the targeted liposomal DXR:C6 combination enabled a 90% death in the case of MDA-MB-231 cells, for an exposure as short as 4 h. This was in contrast with the lack cytotoxic benefit of the (non-liposomal) DXR:Cis combination over each drug alone, against each one of the TNBC cell lines used. Despite increasing concentrations of the DXR:Cis combination, enabled higher (bulk) cell death, the percentage of ALDHhigh viable cells increased by 1.5-fold relative to the untreated control, in the case of MDA-MB-468 cells. Interestingly, the opposite effect was observed for the DXR:C6 combination targeted to nucleolin, where increasing concentrations enabled higher (bulk) cell death, along with a 5-fold decrease of the percentage of viable ALDHhigh putative CSCs (relative to untreated control). These observations were concomitant with alterations of stemness properties favoring the latter. Overall, the enhanced efficacy of the synergistic DXR:C6 combination targeted to nucleolin, enables a significant decrease of the percentage of chemoresistant triple negative breast CSC, besides non-SCCs, in contrast to observations with clinically used drug combination. Thus, this novel strategy offers the potential to address tumor recurrence and drug resistance associated with CSC, in an unmet medical need as TNBC.

Citation Format: Ana F. Cruz, Nuno A. Fonseca, Nélio Gonçalves, Vera Moura, Sérgio Simões, João Nuno Moreira. Differential effect of liposomal C6-ceramide/doxorubicin targeted to nucleolin and conventional combinations against triple negative breast cancer stem cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3622.

Abstract 2994: In vivo targeting of mesothelioma’s molecular signature with nanoparticle functionalized with nucleolin-binding peptide

Mesothelioma is a malignant tumor of the mesothelium, often associated with asbestos exposure, with an overall survival of only 8.8 months. A combination of cisplatin and pemetrexed has been used as an adjuvant treatment to surgical resection or in patients who have inoperable disease. This combination remains as the current standard of care, regardless the sub-type of mesothelioma, with only a 9% 5-year survival rate. Herein, it is hypothesized that a novel targeted treatment, based on a doxorubicin (DXR)-containing nanoparticle functionalized with the nucleolin-binding F3 peptide (named PEGASEMP), will have significant a therapeutic impact against the most aggressive subtype of mesothelioma (biphasic). The hypothesis relies on nucleolin deregulated overexpression in cancer and endothelial cells from tumor blood vessels. Human biphasic mesothelioma cells were stably transduced with luciferase-reporter gene, and orthotopically injected intrapleurally into female immunocompromised mice. Three weeks (Early Stage) and 4 weeks (Advanced Stage) after cell injection, animals were randomly allocated to different treatment groups: vehicle, PEGASEMP at 5.6 or 7 mg of DXR/kg alone (q7dx5w); cisplatin at 4.0 mg/kg alone or combined with PEGASEMP at 5.6 mg of DXR/kg (q7dx5w); and the standard of care, a combination of cisplatin at 4.0 mg/kg (q7dx5w) plus pemetrexed at 100.0 mg/kg (q2dx3x5w). Bioluminescence was monitored weekly with IVIS Spectrum In Vivo Imaging system. Differential gene expression upon PEGASEMP treatment of advanced stage tumors was also performed in comparison with non-treated animals using the GeneChip Human Transcriptome Array 2.0. In the early stage of development, PEGASEMP, at 7.0 mg/kg, inhibited tumor growth by 2,713-fold relative to standard of care, which translated into a 1223-fold decrease in tumor burden. At an advanced stage of tumor development, the combination of PEGASEMP and cisplatin enabled 107-fold tumor growth inhibition, enabling a 55-fold reduction in tumor burden, relative to standard of care. In both cases, no decrease of the body weight was observed. Furthermore, 75% (146) gene transcripts were found to be deregulated (while the remaining 25% were upregulated), involving the downregulation of cell division, including ontologies such as cell cycle or chromatin organization and assembly. Specifically, downregulation of topoisomerase 2, cyclin B1 or Ki67 transcripts, part of the described molecular signature of mesothelioma, was observed and was consistent with the mechanism of action of doxorubicin. Overall, the novel mechanism of action associated with PEGASEMP, enables a significant benefit in terms of efficacy and safety in the treatment of biphasic mesothelioma, as compared with the current standard of care, affecting the molecular signature of the disease and thus supporting future clinical evaluation.

Citation Format: Nuno A. Fonseca, Vera Moura, Fabiana Colelli, Daniela Pesce, Giacomo Signorino, Laura Focareta, Alessandra Fucci, Francesco Cardile, Claudio Pisano, Sérgio Simões, João Nuno Moreira. In vivo targeting of mesothelioma’s molecular signature with nanoparticle functionalized with nucleolin-binding peptide [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2994.

The RNASeq-er API-a gateway to systematically updated analysis of public RNA-seq data

Motivation

The exponential growth of publicly available RNA-sequencing (RNA-Seq) data poses an increasing challenge to researchers wishing to discover, analyse and store such data, particularly those based in institutions with limited computational resources. EMBL-EBI is in an ideal position to address these challenges and to allow the scientific community easy access to not just raw, but also processed RNA-Seq data. We present a Web service to access the results of a systematically and continually updated standardized alignment as well as gene and exon expression quantification of all public bulk (and in the near future also single-cell) RNA-Seq runs in 264 species in European Nucleotide Archive, using Representational State Transfer.

Results

The RNASeq-er API (Application Programming Interface) enables ontology-powered search for and retrieval of CRAM, bigwig and bedGraph files, gene and exon expression quantification matrices (Fragments Per Kilobase Of Exon Per Million Fragments Mapped, Transcripts Per Million, raw counts) as well as sample attributes annotated with ontology terms. To date over 270 00 RNA-Seq runs in nearly 10 000 studies (1PB of raw FASTQ data) in 264 species in ENA have been processed and made available via the API.

Availability and Implementation

The RNASeq-er API can be accessed at http://www.ebi.ac.uk/fg/rnaseq/api . The commands used to analyse the data are available in supplementary materials and at https://github.com/nunofonseca/irap/wiki/iRAP-single-library .

Contact

rnaseq@ebi.ac.uk ; rpetry@ebi.ac.uk.

Supplementary information

Supplementary data are available at Bioinformatics online.

Inferences on specificity recognition at the Malus×domestica gametophytic self-incompatibility system

In Malus × domestica (Rosaceae) the product of each SFBB gene (the pollen component of the gametophytic self-incompatibility (GSI) system) of a S-haplotype (the combination of pistil and pollen genes that are linked) interacts with a sub-set of non-self S-RNases (the pistil component), but not with the self S-RNase. To understand how the Malus GSI system works, we identified 24 SFBB genes expressed in anthers, and determined their gene sequence in nine M. domestica cultivars. Expression of these SFBBs was not detected in the petal, sepal, filament, receptacle, style, stigma, ovary or young leaf. For all SFBBs (except SFBB15), identical sequences were obtained only in cultivars having the same S-RNase. Linkage with a particular S-RNase was further established using the progeny of three crosses. Such data is needed to understand how other genes not involved in GSI are affected by the S-locus region. To classify SFBBs specificity, the amino acids under positive selection obtained when performing intra-haplotypic analyses were used. Using this information and the previously identified S-RNase positively selected amino acid sites, inferences are made on the S-RNase amino acid properties (hydrophobicity, aromatic, aliphatic, polarity, and size), at these positions, that are critical features for GSI specificity determination.

Expression Atlas: gene and protein expression across multiple studies and organisms

Expression Atlas (http://www.ebi.ac.uk/gxa) is an added value database that provides information about gene and protein expression in different species and contexts, such as tissue, developmental stage, disease or cell type. The available public and controlled access data sets from different sources are curated and re-analysed using standardized, open source pipelines and made available for queries, download and visualization. As of August 2017, Expression Atlas holds data from 3,126 studies across 33 different species, including 731 from plants. Data from large-scale RNA sequencing studies including Blueprint, PCAWG, ENCODE, GTEx and HipSci can be visualized next to each other. In Expression Atlas, users can query genes or gene-sets of interest and explore their expression across or within species, tissues, developmental stages in a constitutive or differential context, representing the effects of diseases, conditions or experimental interventions. All processed data matrices are available for direct download in tab-delimited format or as R-data. In addition to the web interface, data sets can now be searched and downloaded through the Expression Atlas R package. Novel features and visualizations include the on-the-fly analysis of gene set overlaps and the option to view gene co-expression in experiments investigating constitutive gene expression across tissues or other conditions.

Two independent modes of chromatin organization revealed by cohesin removal

Imaging and chromosome conformation capture studies have revealed several layers of chromosome organization, including segregation into megabase-sized active and inactive compartments, and partitioning into sub-megabase domains (TADs). It remains unclear, however, how these layers of organization form, interact with one another and influence genome function. Here we show that deletion of the cohesin-loading factor Nipbl in mouse liver leads to a marked reorganization of chromosomal folding. TADs and associated Hi-C peaks vanish globally, even in the absence of transcriptional changes. By contrast, compartmental segregation is preserved and even reinforced. Strikingly, the disappearance of TADs unmasks a finer compartment structure that accurately reflects the underlying epigenetic landscape. These observations demonstrate that the three-dimensional organization of the genome results from the interplay of two independent mechanisms: cohesin-independent segregation of the genome into fine-scale compartments, defined by chromatin state; and cohesin-dependent formation of TADs, possibly by loop extrusion, which helps to guide distant enhancers to their target genes.

Abstract 389: Integrating diverse transcriptomic alterations to identify cancer-relevant genes

Introduction:

We present a novel method to identify cancer driver genes that jointly examines any number of diverse transcriptomic alterations with the goal to uncover highly recurrent and heterogeneous patterns in 1190 samples across 26 cancer types as part of the PanCancer Analysis of Whole Genomes (PCAWG) of the International Cancer Genome Consortium (ICGC).

Motivation:

Previous pan-cancer genomic studies have focused on the analysis of somatic mutations as the driver of phenotypic changes. Here, we propose a method to integrate a wide variety of RNA and DNA changes to redefine the concept of driver events and account for the transcriptome’s role in tumorigenesis. PTK2 provides a motivating example, since it has many RNA alterations that correlate with patient survival, such as overexpression, exon-skips, and alternative promoter usage.

In our analysis, we integrate an unprecedented amount of various alterations including gene fusions, RNA editing, alternative splicing, expression outliers, alternative promoters, allele specific expression, and somatic mutations. This enables us to also identify mutually exclusive (MutE) and co-occurring (CoO) patterns between different types of alterations within a gene.

Methods:

Our method has 3 main strengths: flexibility to handle any number or type of alteration, sensitivity to different frequencies of alterations so rare events are not lost in the recurrence analysis, and diversity of ranking such that genes with multiple alterations are prioritized. Our method is summarized in two steps:

1) Identify genes that are both recurrently and heterogeneously altered across many samples by calculating a rank-based score for each gene.

2) Identify MutE and CoO patterns between alteration types for the genes identified in the previous step.

To ensure that alterations were comparable, we applied a thresholding model to binarize all alterations for gene-sample pairs, allowing us to account for the properties of the different modalities involved.

Step 1 of our method calculates a score for each gene that takes into account: 1) the number of alterations to a gene across all samples, 2) the rarity of each alteration, and 3) how many types of alterations are observed per gene. The score is then used to rank the genes and top genes are considered for MutE and CoO analyses.

Results:

Our top 100 ranked genes were highly enriched for cancer census genes (adjusted p-value: 2.06e-9), indicating that we identify cancer relevant genes. Our top five ranked cancer census genes were IGF2, ERBB2, RARA, CREBBP, and ARID1A; all of which had at least 4 of 7 possible alterations, showing our scoring method prioritizes genes with diverse alterations. We also found that alternative promoter usage and alternative splicing were highly co-occurring alterations, with PTK2 having the highest co-occurrence between them. In summary, we propose a new method to analyze various RNA disruptions and show it can yield new insights beyond genomic variation.

Citation Format: Natalie R. Davidson, PanCancer Analysis of Whole Genomes 3 (PCAWG-3) for ICGC, Alvis Brazma, Angela N. Brooks, Claudia Calabrese, Nuno A. Fonseca, Jonathan Goke, Yao He, Xueda Hu, Andre Kahles, Kjong-Van Lehmann, Fenglin Liu, Gunnar Rätsch, Siliang Li, Roland F. Schwarz, Mingyu Yang, Zemin Zhang, Fan Zhang, Liangtao Zheng. Integrating diverse transcriptomic alterations to identify cancer-relevant genes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 389. doi:10.1158/1538-7445.AM2017-389

The cancer stem cell phenotype as a determinant factor of the heterotypic nature of breast tumors

Gathering evidence supports the existence of a population of cells with stem-like characteristics, named cancer stem cells (CSC), which is involved not only in tumor recurrence but also in tumorigenicity, metastization and drug resistance. Several markers have been used to identify putative CSC sub-populations in different cancers. Notwithstanding, it has been acknowledged that breast CSC may originate from non-stem cancer cells (non-SCC), interconverting through an epithelial-to-mesenchymal transition-mediated process, and presenting several deregulated canonical and developmental signaling pathways. These support the heterogeneity that, directly or indirectly, influences fundamental biological features supporting breast tumor development. Accordingly, CSC have increasingly become highly relevant cellular targets. In this review, we will address the stemness concept in cancer, setting the perspective on CSC and their origin, by exploring their relation and regulation within the tumor microenvironment, in the context of emerging therapeutic targets. Within this framework, we will discuss nucleolin, a protein that has been associated with angiogenesis and, more recently, with the stemness phenotype, becoming a common denominator between CSC and non-SCC for multicellular targeting.

Inoculated Cell Density as a Determinant Factor of the Growth Dynamics and Metastatic Efficiency of a Breast Cancer Murine Model

4T1 metastatic breast cancer model have been widely used to study stage IV human breast cancer. However, the frequent inoculation of a large number of cells, gives rise to fast growing tumors, as well as to a surprisingly low metastatic take rate. The present work aimed at establishing the conditions enabling high metastatic take rate of the triple-negative murine 4T1 syngeneic breast cancer model. An 87% 4T1 tumor incidence was observed when as few as 500 cancer cells were implanted. 4T1 cancer cells colonized primarily the lungs with 100% efficiency, and distant lesions were also commonly identified in the mesentery and pancreas. The drastic reduction of the number of inoculated cells resulted in increased tumor doubling times and decreased specific growth rates, following a Gompertzian tumor expansion. The established conditions for the 4T1 mouse model were further validated in a therapeutic study with peguilated liposomal doxorubicin, in clinical used in the setting of metastatic breast cancer. Inoculated cell density was proven to be a key methodological aspect towards the reproducible development of macrometastases in the 4T1 mouse model and a more reliable pre-clinical assessment of antimetastatic therapies.

Expression Atlas update--an integrated database of gene and protein expression in humans, animals and plants

Expression Atlas (http://www.ebi.ac.uk/gxa) provides information about gene and protein expression in animal and plant samples of different cell types, organism parts, developmental stages, diseases and other conditions. It consists of selected microarray and RNA-sequencing studies from ArrayExpress, which have been manually curated, annotated with ontology terms, checked for high quality and processed using standardised analysis methods. Since the last update, Atlas has grown seven-fold (1572 studies as of August 2015), and incorporates baseline expression profiles of tissues from Human Protein Atlas, GTEx and FANTOM5, and of cancer cell lines from ENCODE, CCLE and Genentech projects. Plant studies constitute a quarter of Atlas data. For genes of interest, the user can view baseline expression in tissues, and differential expression for biologically meaningful pairwise comparisons-estimated using consistent methodology across all of Atlas. Our first proteomics study in human tissues is now displayed alongside transcriptomics data in the same tissues. Novel analyses and visualisations include: 'enrichment' in each differential comparison of GO terms, Reactome, Plant Reactome pathways and InterPro domains; hierarchical clustering (by baseline expression) of most variable genes and experimental conditions; and, for a given gene-condition, distribution of baseline expression across biological replicates.

Dual release of a hydrophilic and a hydrophobic osteogenic factor from a single liposome

Dual release of growth/differentiation factors from liposomes induced osteogenic differentiation of mesenchymal stem cells.

Gramene 2016: comparative plant genomics and pathway resources

Gramene (http://www.gramene.org) is an online resource for comparative functional genomics in crops and model plant species. Its two main frameworks are genomes (collaboration with Ensembl Plants) and pathways (The Plant Reactome and archival BioCyc databases). Since our last NAR update, the database website adopted a new Drupal management platform. The genomes section features 39 fully assembled reference genomes that are integrated using ontology-based annotation and comparative analyses, and accessed through both visual and programmatic interfaces. Additional community data, such as genetic variation, expression and methylation, are also mapped for a subset of genomes. The Plant Reactome pathway portal (http://plantreactome.gramene.org) provides a reference resource for analyzing plant metabolic and regulatory pathways. In addition to ∼ 200 curated rice reference pathways, the portal hosts gene homology-based pathway projections for 33 plant species. Both the genome and pathway browsers interface with the EMBL-EBI's Expression Atlas to enable the projection of baseline and differential expression data from curated expression studies in plants. Gramene's archive website (http://archive.gramene.org) continues to provide previously reported resources on comparative maps, markers and QTL. To further aid our users, we have also introduced a live monthly educational webinar series and a Gramene YouTube channel carrying video tutorials.

Nucleolin overexpression in breast cancer cell sub-populations with different stem-like phenotype enables targeted intracellular delivery of synergistic drug combination

Breast cancer stem cells (CSC) are thought responsible for tumor growth and relapse, metastization and active evasion to standard chemotherapy. The recognition that CSC may originate from non-stem cancer cells (non-SCC) through plastic epithelial-to-mesenchymal transition turned these into relevant cell targets. Of crucial importance for successful therapeutic intervention is the identification of surface receptors overexpressed in both CSC and non-SCC. Cell surface nucleolin has been described as overexpressed in cancer cells as well as a tumor angiogenic marker. Herein we have addressed the questions on whether nucleolin was a common receptor among breast CSC and non-SCC and whether it could be exploited for targeting purposes. Liposomes functionalized with the nucleolin-binding F3 peptide, targeted simultaneously, nucleolin-overexpressing putative breast CSC and non-SCC, which was paralleled by OCT4 and NANOG mRNA levels in cells from triple negative breast cancer (TNBC) origin. In murine embryonic stem cells, both nucleolin mRNA levels and F3 peptide-targeted liposomes cellular association were dependent on the stemness status. An in vivo tumorigenic assay suggested that surface nucleolin overexpression per se, could be associated with the identification of highly tumorigenic TNBC cells. This proposed link between nucleolin expression and the stem-like phenotype in TNBC, enabled 100% cell death mediated by F3 peptide-targeted synergistic drug combination, suggesting the potential to abrogate the plasticity and adaptability associated with CSC and non-SCC. Ultimately, nucleolin-specific therapeutic tools capable of simultaneous debulk multiple cellular compartments of the tumor microenvironment may pave the way towards a specific treatment for TNBC patient care.

Predicting malignancy from mammography findings and image-guided core biopsies

The main goal of this work is to produce machine learning models that predict the outcome of a mammography from a reduced set of annotated mammography findings. In the study we used a dataset consisting of 348 consecutive breast masses that underwent image guided core biopsy performed between October 2005 and December 2007 on 328 female subjects. We applied various algorithms with parameter variation to learn from the data. The tasks were to predict mass density and to predict malignancy. The best classifier that predicts mass density is based on a support vector machine and has accuracy of 81.3%. The expert correctly annotated 70% of the mass densities. The best classifier that predicts malignancy is also based on a support vector machine and has accuracy of 85.6%, with a positive predictive value of 85%. One important contribution of this work is that our model can predict malignancy in the absence of the mass density attribute, since we can fill up this attribute using our mass density predictor.

Convergent evolution at the gametophytic self-incompatibility system in Malus and Prunus

S-RNase-based gametophytic self-incompatibility (GSI) has evolved once before the split of the Asteridae and Rosidae. This conclusion is based on the phylogenetic history of the S-RNase that determines pistil specificity. In Rosaceae, molecular characterizations of Prunus species, and species from the tribe Pyreae (i.e., Malus, Pyrus, Sorbus) revealed different numbers of genes determining S-pollen specificity. In Prunus only one pistil and pollen gene determine GSI, while in Pyreae there is one pistil but multiple pollen genes, implying different specificity recognition mechanisms. It is thus conceivable that within Rosaceae the genes involved in GSI in the two lineages are not orthologous but possibly paralogous. To address this hypothesis we characterised the S-RNase lineage and S-pollen lineage genes present in the genomes of five Rosaceae species from three genera: M. × domestica (apple, self-incompatible (SI); tribe Pyreae), P. persica (peach, self-compatible (SC); Amygdaleae), P. mume (mei, SI; Amygdaleae), Fragaria vesca (strawberry, SC; Potentilleae), and F. nipponica (mori-ichigo, SI; Potentilleae). Phylogenetic analyses revealed that the Malus and Prunus S-RNase and S-pollen genes belong to distinct gene lineages, and that only Prunus S-RNase and SFB-lineage genes are present in Fragaria. Thus, S-RNase based GSI system of Malus evolved independently from the ancestral system of Rosaceae. Using expression patterns based on RNA-seq data, the ancestral S-RNase lineage gene is inferred to be expressed in pistils only, while the ancestral S-pollen lineage gene is inferred to be expressed in tissues other than pollen.

Antibacterial activity of chitosan nanofiber meshes with liposomes immobilized releasing gentamicin

Chitsan (Ch) nanofiber mesh (NFM) is a material with natural characteristics favoring its use in human wound dressing. The present work proposes a gentamicin-loaded liposome immobilized at the surface of Ch NFMs to promote its antibacterial activity. To achieve this purpose, Ch NFMs were functionalized with thiol groups, and gentamicin-loaded liposomes were covalently immobilized by the reaction of the SH groups with maleimide. The maximum concentration of SH groups (55.52±11.19nmolcm(-2)) was obtained at pH 7. A fluorescent dye was covalently bound to the SH groups present at the surface of electrospun Ch NFMs. Their spatial distribution was uniform throughout the NFMs when analyzed by fluorescence microscopy. Gentamicin was successfully encapsulated into the liposomes with an efficiency of 17%. Gentamicin-loaded liposomes were uniformly distributed at the surface of the Ch NFMs and the drug release kinetic showed a sustained release of gentamicin during 16h, achieving a steady state at 24h. The in vitro susceptibility tests confirmed that the gentamicin released from the liposomes immobilized at the surface of electrospun Ch NFM has bactericidal activity against Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus. The results show that the developed system has promising performance for wound dressing applications, avoiding infections caused by these common pathogens.

RNA-Seq gene profiling--a systematic empirical comparison

Accurately quantifying gene expression levels is a key goal of experiments using RNA-sequencing to assay the transcriptome. This typically requires aligning the short reads generated to the genome or transcriptome before quantifying expression of pre-defined sets of genes. Differences in the alignment/quantification tools can have a major effect upon the expression levels found with important consequences for biological interpretation. Here we address two main issues: do different analysis pipelines affect the gene expression levels inferred from RNA-seq data? And, how close are the expression levels inferred to the "true" expression levels? We evaluate fifty gene profiling pipelines in experimental and simulated data sets with different characteristics (e.g, read length and sequencing depth). In the absence of knowledge of the 'ground truth' in real RNAseq data sets, we used simulated data to assess the differences between the "true" expression and those reconstructed by the analysis pipelines. Even though this approach does not take into account all known biases present in RNAseq data, it still allows to estimate the accuracy of the gene expression values inferred by different analysis pipelines. The results show that i) overall there is a high correlation between the expression levels inferred by the best pipelines and the true quantification values; ii) the error in the estimated gene expression values can vary considerably across genes; and iii) a small set of genes have expression estimates with consistently high error (across data sets and methods). Finally, although the mapping software is important, the quantification method makes a greater difference to the results.

Instructive nanofibrous scaffold comprising runt-related transcription factor 2 gene delivery for bone tissue engineering

Inducer molecules capable of regulating mesenchymal stem cell differentiation into specific lineages have proven effective in basic science and in preclinical studies. Runt-related transcription factor 2 (RUNX2) is considered to be the central gene involved in the osteoblast phenotype induction, which may be advantageous for inducing bone tissue regeneration. This work envisions the development of a platform for gene delivery, combining liposomes as gene delivery devices, with electrospun nanofiber mesh (NFM) as a tissue engineering scaffold. pDNA-loaded liposomes were immobilized at the surface of functionalized polycaprolactone (PCL) NFM. Human bone-marrow-derived mesenchymal stem cells (hBMSCs) cultured on RUNX2-loaded liposomes immobilized at the surface of electrospun PCL NFM showed enhanced levels of metabolic activity and total protein synthesis. RUNX2-loaded liposomes immobilized at the surface of electrospun PCL NFMs induce a long-term gene expression of eGFP and RUNX2 by cultured hBMSCs. Furthermore, osteogenic differentiation of hBMSCs was also achieved by the overexpression of other osteogenic markers in medium free of osteogenic supplementation. These findings demonstrate that surface immobilization of RUNX2 plasmid onto elestrospun PCL NFM can produce long-term gene expression in vitro, which may be employed to enhance the osteoinductive properties of scaffolds used for bone tissue engineering strategies.

High-resolution mapping of transcriptional dynamics across tissue development reveals a stable mRNA-tRNA interface

The genetic code is an abstraction of how mRNA codons and tRNA anticodons molecularly interact during protein synthesis; the stability and regulation of this interaction remains largely unexplored. Here, we characterized the expression of mRNA and tRNA genes quantitatively at multiple time points in two developing mouse tissues. We discovered that mRNA codon pools are highly stable over development and simply reflect the genomic background; in contrast, precise regulation of tRNA gene families is required to create the corresponding tRNA transcriptomes. The dynamic regulation of tRNA genes during development is controlled in order to generate an anticodon pool that closely corresponds to messenger RNAs. Thus, across development, the pools of mRNA codons and tRNA anticodons are invariant and highly correlated, revealing a stable molecular interaction interlocking transcription and translation.

Bridging cancer biology and the patients' needs with nanotechnology-based approaches

Cancer remains as stressful condition and a leading cause of death in the western world. Actual cornerstone treatments of cancer disease rest as an elusive alternative, offering limited efficacy with extensive secondary effects as a result of severe cytotoxic effects in healthy tissues. The advent of nanotechnology brought the promise to revolutionize many fields including oncology, proposing advanced systems for cancer treatment. Drug delivery systems rest among the most successful examples of nanotechnology. Throughout time they have been able to evolve as a function of an increased understanding from cancer biology and the tumor microenvironment. Marketing of Doxil® unleashed a remarkable impulse in the development of drug delivery systems. Since then, several nanocarriers have been introduced, with aspirations to overrule previous technologies, demonstrating increased therapeutic efficacy besides decreased toxicity. Spatial and temporal targeting to cancer cells has been explored, as well as the use of drug combinations co-encapsulated in the same particle as a mean to take advantage of synergistic interactions in vivo. Importantly, targeted delivery of siRNA for gene silencing therapy has made its way to the clinic for a "first in man" trial using lipid-polymeric-based particles. Focusing in state-of-the-art technology, this review will provide an insightful vision on nanotechnology-based strategies for cancer treatment, approaching them from a tumor biology-driven perspective, since their early EPR-based dawn to the ones that have truly the potential to address unmet medical needs in the field of oncology, upon targeting key cell subpopulations from the tumor microenvironment.

Immobilization of bioactive factor-loaded liposomes on the surface of electrospun nanofibers targeting tissue engineering

Dexamethasone-loaded liposomes immobilized at the surface of electrospun polycaprolactone nanofiber meshes successfully promoted the osteogenic differentiation of human bone marrow-derived mesenchymal stem cells.

Expression Atlas update--a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments

Expression Atlas (http://www.ebi.ac.uk/gxa) is a value-added database providing information about gene, protein and splice variant expression in different cell types, organism parts, developmental stages, diseases and other biological and experimental conditions. The database consists of selected high-quality microarray and RNA-sequencing experiments from ArrayExpress that have been manually curated, annotated with Experimental Factor Ontology terms and processed using standardized microarray and RNA-sequencing analysis methods. The new version of Expression Atlas introduces the concept of 'baseline' expression, i.e. gene and splice variant abundance levels in healthy or untreated conditions, such as tissues or cell types. Differential gene expression data benefit from an in-depth curation of experimental intent, resulting in biologically meaningful 'contrasts', i.e. instances of differential pairwise comparisons between two sets of biological replicates. Other novel aspects of Expression Atlas are its strict quality control of raw experimental data, up-to-date RNA-sequencing analysis methods, expression data at the level of gene sets, as well as genes and a more powerful search interface designed to maximize the biological value provided to the user.

On the use of dexamethasone-loaded liposomes to induce the osteogenic differentiation of human mesenchymal stem cells

Stem cells have received considerable attention by the scientific community because of their potential for tissue engineering and regenerative medicine. The most frequently used method to promote their differentiation is supplementation of the in vitro culture medium with growth/differentiation factors (GDFs). The limitations of that strategy caused by the short half-life of GDFs limit its efficacy in vivo and consequently its clinical use. Thus, the development of new concepts that enable the bioactivity and bioavailability of GDFs to be protected, both in vitro and in vivo, is very relevant. Nanoparticle-based drug delivery systems can be injected, protect the GDFs and enable spatiotemporal release kinetics to be controlled. Liposomes are well-established nanodelivery devices presenting significant advantages, viz. a high load-carrying capacity, relative safety and easy production, and a versatile nature in terms of possible formulations and surface functionalization. The main objective of the present study was to optimize the formulation of liposomes to encapsulate dexamethasone (Dex). Our results showed that the optimized Dex-loaded liposomes do not have any cytotoxic effect on human bone marrow-derived mesenchymal stem cells (hBMSCs). More importantly, they were able to promote an earlier induction of differentiation of hBMSCs into the osteogenic lineage, as demonstrated by the expression of osteoblastic markers, both phenotypically and genotypically. We concluded that Dex-loaded liposomes represent a viable nanoparticle strategy with enhanced safety and efficacy for tissue engineering and regenerative medicine.