RNAdetector: a free user-friendly stand-alone and cloud-based system for RNA-Seq data analysis.

BACKGROUND: RNA-Seq is a well-established technology extensively used for transcriptome profiling, allowing the analysis of coding and non-coding RNA molecules. However, this technology produces a vast amount of data requiring sophisticated computational approaches for their analysis than other traditional technologies such as Real-Time PCR or microarrays, strongly discouraging non-expert users. For this reason, dozens of pipelines have been deployed for the analysis of RNA-Seq data. Although interesting, these present several limitations and their usage require a technical background, which may be uncommon in small research laboratories. Therefore, the application of these technologies in such contexts is still limited and causes a clear bottleneck in knowledge advancement. RESULTS: Motivated by these considerations, we have developed RNAdetector, a new free cross-platform and user-friendly RNA-Seq data analysis software that can be used locally or in cloud environments through an easy-to-use Graphical User Interface allowing the analysis of coding and non-coding RNAs from RNA-Seq datasets of any sequenced biological species. CONCLUSIONS: RNAdetector is a new software that fills an essential gap between the needs of biomedical and research labs to process RNA-Seq data and their common lack of technical background in performing such analysis, which usually relies on outsourcing such steps to third party bioinformatics facilities or using expensive commercial software.

Mining potentially actionable kinase gene fusions in cancer cell lines with the KuNG FU database.

Inhibition of kinase gene fusions (KGFs) has proven successful in cancer treatment and continues to represent an attractive research area, due to kinase druggability and clinical validation. Indeed, literature and public databases report a remarkable number of KGFs as potential drug targets, often identified by in vitro characterization of tumor cell line models and confirmed also in clinical samples. However, KGF molecular and experimental information can sometimes be sparse and partially overlapping, suggesting the need for a specific annotation database of KGFs, conveniently condensing all the molecular details that can support targeted drug development pipelines and diagnostic approaches. Here, we describe KuNG FU (KiNase Gene FUsion), a manually curated database collecting detailed annotations on KGFs that were identified and experimentally validated in human cancer cell lines from multiple sources, exclusively focusing on in-frame KGF events retaining an intact kinase domain, representing potentially active driver kinase targets. To our knowledge, KuNG FU represents to date the largest freely accessible homogeneous and curated database of kinase gene fusions in cell line models.

A benchmarking of pipelines for detecting ncRNAs from RNA-Seq data.

Next-Generation Sequencing (NGS) is a high-throughput technology widely applied to genome sequencing and transcriptome profiling. RNA-Seq uses NGS to reveal RNA identities and quantities in a given sample. However, it produces a huge amount of raw data that need to be preprocessed with fast and effective computational methods. RNA-Seq can look at different populations of RNAs, including ncRNAs. Indeed, in the last few years, several ncRNAs pipelines have been developed for ncRNAs analysis from RNA-Seq experiments. In this paper, we analyze eight recent pipelines (iSmaRT, iSRAP, miARma-Seq, Oasis 2, SPORTS1.0, sRNAnalyzer, sRNApipe, sRNA workbench) which allows the analysis not only of single specific classes of ncRNAs but also of more than one ncRNA classes. Our systematic performance evaluation aims at guiding users to select the appropriate pipeline for processing each ncRNA class, focusing on three key points: (i) accuracy in ncRNAs identification, (ii) accuracy in read count estimation and (iii) deployment and ease of use.

Comprehensive kinome NGS targeted expression profiling by KING-REX.

BACKGROUND: Protein kinases are enzymes controlling different cellular functions. Genetic alterations often result in kinase dysregulation, making kinases a very attractive class of druggable targets in several human diseases. Existing approved drugs still target a very limited portion of the human 'kinome', demanding a broader functional knowledge of individual and co-expressed kinase patterns in physiologic and pathologic settings. The development of novel rapid and cost-effective methods for kinome screening is therefore highly desirable, potentially leading to the identification of novel kinase drug targets. RESULTS: In this work, we describe the development of KING-REX (KINase Gene RNA EXpression), a comprehensive kinome RNA targeted custom assay-based panel designed for Next Generation Sequencing analysis, coupled with a dedicated data analysis pipeline. We have conceived KING-REX for the gene expression analysis of 512 human kinases; for 319 kinases, paired assays and custom analysis pipeline features allow the evaluation of 3'- and 5'-end transcript imbalances as readout for the prediction of gene rearrangements. Validation tests on cell line models harboring known gene fusions demonstrated a comparable accuracy of KING-REX gene expression assessment as in whole transcriptome analyses, together with a robust detection of transcript portion imbalances in rearranged kinases, even in complex RNA mixtures or in degraded RNA. CONCLUSIONS: These results support the use of KING-REX as a rapid and cost effective kinome investigation tool in the field of kinase target identification for applications in cancer biology and other human diseases.

Afatinib Is a New Therapeutic Approach in Chordoma with a Unique Ability to Target EGFR and Brachyury.

Chordomas are rare bone tumors with no approved therapy. These tumors express several activated tyrosine kinase receptors, which prompted attempts to treat patients with tyrosine kinase inhibitors. Although clinical benefit was observed in phase II clinical trials with imatinib and sorafenib, and sporadically also with EGFR inhibitors, therapies evaluated to date have shown modest activity. With the goal of identifying new drugs with immediate therapeutic potential for chordoma patients, we collected clinically approved drugs and other advanced inhibitors of MET, PDGFRß, and EGFR tyrosine kinases, and assessed their antiproliferative activity against a panel of chordoma cell lines. Chordoma cell lines were not responsive to MET and PDGFRß inhibitors. U-CH1 and UM-Chor1 were sensitive to all EGFR inhibitors, whereas the remaining cell lines were generally insensitive to these drugs. Afatinib was the only EGFR inhibitor with activity across the chordoma panel. We then investigated the molecular mechanisms behind the responses observed and found that the antiproliferative IC50s correlate with the unique ability of afatinib to promote degradation of EGFR and brachyury, an embryonic transcription factor considered a key driver of chordoma. Afatinib displayed potent antitumor efficacy in U-CH1, SF8894, CF322, and CF365 chordoma tumor models in vivo In the panel analyzed, high EGFR phosphorylation and low AXL and STK33 expression correlated with higher sensitivity to afatinib and deserve further investigation as potential biomarkers of response. These data support the use of afatinib in clinical trials and provide the rationale for the upcoming European phase II study on afatinib in advanced chordoma. Mol Cancer Ther; 17(3); 603-13. ©2017 AACR.

Identification and characterization of a novel SCYL3-NTRK1 rearrangement in a colorectal cancer patient.

In colorectal cancer patients, chromosomal rearrangements involving NTRK1 gene (encoding the TRKA protein) are shown in a small subset of patients and are associated with the constitutive activation of the kinase domain of TRKA. In turn, activated TRKA-fusion proteins are associated with proliferation and survival in colorectal cancer tumors. Here we report the identification and functional characterization of a new SCYL3-NTRK1 fusion gene in a 61-year-old colorectal cancer patient. To our knowledge, this fusion protein has never been previously documented in oncological patients. We show that this novel fusion is oncogenic and sensitive to TRKA inhibitors. As suggested by other pieces of evidence, entrectinib - an orally available pan-TRK, ROS1 and ALK inhibitor - may have particular efficacy in patients with NTRK rearrangements. Therefore, screening for rearrangements involving NTRK genes may help identifying a subset of patients able to derive benefit from treatment with entrectinib or other targeted inhibitors.

Establishment and genomic characterization of the new chordoma cell line Chor-IN-1.

Chordomas are rare, slowly growing tumors with high medical need, arising in the axial skeleton from notochord remnants. The transcription factor "brachyury" represents a distinctive molecular marker and a key oncogenic driver of chordomas. Tyrosine kinase receptors are also expressed, but so far kinase inhibitors have not shown clear clinical efficacy in chordoma patients. The need for effective therapies is extremely high, but the paucity of established chordoma cell lines has limited preclinical research. Here we describe the isolation of the new Chor-IN-1 cell line from a recurrent sacral chordoma and its characterization as compared to other chordoma cell lines. Chor-IN-1 displays genomic identity to the tumor of origin and has morphological features, growth characteristics and chromosomal abnormalities typical of chordoma, with expression of brachyury and other relevant biomarkers. Chor-IN-1 gene variants, copy number alterations and kinome gene expression were analyzed in comparison to other four chordoma cell lines, generating large scale DNA and mRNA genomic data that can be exploited for the identification of novel pharmacological targets and candidate predictive biomarkers of drug sensitivity in chordoma. The establishment of this new, well characterized chordoma cell line provides a useful tool for the identification of drugs active in chordoma.

Computational drugs repositioning identifies inhibitors of oncogenic PI3K/AKT/P70S6K-dependent pathways among FDA-approved compounds.

The discovery of inhibitors for oncogenic signalling pathways remains a key focus in modern oncology, based on personalized and targeted therapeutics. Computational drug repurposing via the analysis of FDA-approved drug network is becoming a very effective approach to identify therapeutic opportunities in cancer and other human diseases. Given that gene expression signatures can be associated with specific oncogenic mutations, we tested whether a "reverse" oncogene-specific signature might assist in the computational repositioning of inhibitors of oncogenic pathways. As a proof of principle, we focused on oncogenic PI3K-dependent signalling, a molecular pathway frequently driving cancer progression as well as raising resistance to anticancer-targeted therapies. We show that implementation of "reverse" oncogenic PI3K-dependent transcriptional signatures combined with interrogation of drug networks identified inhibitors of PI3K-dependent signalling among FDA-approved compounds. This led to repositioning of Niclosamide (Niclo) and Pyrvinium Pamoate (PP), two anthelmintic drugs, as inhibitors of oncogenic PI3K-dependent signalling. Niclo inhibited phosphorylation of P70S6K, while PP inhibited phosphorylation of AKT and P70S6K, which are downstream targets of PI3K. Anthelmintics inhibited oncogenic PI3K-dependent gene expression and showed a cytostatic effect in vitro and in mouse mammary gland. Lastly, PP inhibited the growth of breast cancer cells harbouring PI3K mutations. Our data indicate that drug repositioning by network analysis of oncogene-specific transcriptional signatures is an efficient strategy for identifying oncogenic pathway inhibitors among FDA-approved compounds. We propose that PP and Niclo should be further investigated as potential therapeutics for the treatment of tumors or diseases carrying the constitutive activation of the PI3K/P70S6K signalling axis.

Entrectinib, a Pan-TRK, ROS1, and ALK Inhibitor with Activity in Multiple Molecularly Defined Cancer Indications.

Activated ALK and ROS1 tyrosine kinases, resulting from chromosomal rearrangements, occur in a subset of non-small cell lung cancers (NSCLC) as well as other tumor types and their oncogenic relevance as actionable targets has been demonstrated by the efficacy of selective kinase inhibitors such as crizotinib, ceritinib, and alectinib. More recently, low-frequency rearrangements of TRK kinases have been described in NSCLC, colorectal carcinoma, glioblastoma, and Spitzoid melanoma. Entrectinib, whose discovery and preclinical characterization are reported herein, is a novel, potent inhibitor of ALK, ROS1, and, importantly, of TRK family kinases, which shows promise for therapy of tumors bearing oncogenic forms of these proteins. Proliferation profiling against over 200 human tumor cell lines revealed that entrectinib is exquisitely potent in vitro against lines that are dependent on the drug's pharmacologic targets. Oral administration of entrectinib to tumor-bearing mice induced regression in relevant human xenograft tumors, including the TRKA-dependent colorectal carcinoma KM12, ROS1-driven tumors, and several ALK-dependent models of different tissue origins, including a model of brain-localized lung cancer metastasis. Entrectinib is currently showing great promise in phase I/II clinical trials, including the first documented objective responses to a TRK inhibitor in colorectal carcinoma and in NSCLC. The drug is, thus, potentially suited to the therapy of several molecularly defined cancer settings, especially that of TRK-dependent tumors, for which no approved drugs are currently available. Mol Cancer Ther; 15(4); 628-39. ©2016 AACR.

Sensitivity to Entrectinib Associated With a Novel LMNA-NTRK1 Gene Fusion in Metastatic Colorectal Cancer.

In metastatic colorectal cancer (CRC), actionable genetic lesions represent potential clinical opportunities. NTRK1, 2, and 3 gene rearrangements encode oncogenic fusions of the tropomyosin-receptor kinase (TRK) family of receptor tyrosine kinases in different tumor types. The TPM3-NTRK1 rearrangement is a recurring event in CRC that renders tumors sensitive to TRKA kinase inhibitors in preclinical models. We identified abnormal expression of the TRKA protein in tumor and liver metastases of a CRC patient refractory to standard therapy. Molecular characterization unveiled a novel LMNA-NTRK1 rearrangement within chromosome 1 with oncogenic potential, and the patient was treated with the pan-TRK inhibitor entrectinib, achieving partial response with decrease in hepatic target lesions from 6.8 and 8.2cm in longest diameter to 4.7 and 4.3cm, respectively. To our knowledge, this is the first clinical evidence of efficacy for therapeutic inhibition of TRKA in a solid tumor, illuminating a genomic-driven strategy to identify CRCs reliant on this oncogene to be clinically targeted with entrectinib.

KAOS: a new automated computational method for the identification of overexpressed genes.

BACKGROUND: Kinase over-expression and activation as a consequence of gene amplification or gene fusion events is a well-known mechanism of tumorigenesis. The search for novel rearrangements of kinases or other druggable genes may contribute to understanding the biology of cancerogenesis, as well as lead to the identification of new candidate targets for drug discovery. However this requires the ability to query large datasets to identify rare events occurring in very small fractions (1-3 %) of different tumor subtypes. This task is different from what is normally done by conventional tools that are able to find genes differentially expressed between two experimental conditions. RESULTS: We propose a computational method aimed at the automatic identification of genes which are selectively over-expressed in a very small fraction of samples within a specific tissue. The method does not require a healthy counterpart or a reference sample for the analysis and can be therefore applied also to transcriptional data generated from cell lines. In our implementation the tool can use gene-expression data from microarray experiments, as well as data generated by RNASeq technologies. CONCLUSIONS: The method was implemented as a publicly available, user-friendly tool called KAOS (Kinase Automatic Outliers Search). The tool enables the automatic execution of iterative searches for the identification of extreme outliers and for the graphical visualization of the results. Filters can be applied to select the most significant outliers. The performance of the tool was evaluated using a synthetic dataset and compared to state-of-the-art tools. KAOS performs particularly well in detecting genes that are overexpressed in few samples or when an extreme outlier stands out on a high variable expression background. To validate the method on real case studies, we used publicly available tumor cell line microarray data, and we were able to identify genes which are known to be overexpressed in specific samples, as well as novel ones.

Novel CAD-ALK gene rearrangement is drugable by entrectinib in colorectal cancer.

BACKGROUND: Activated anaplastic lymphoma kinase (ALK) gene fusions are recurrent events in a small fraction of colorectal cancers (CRCs), although these events have not yet been exploited as in other malignancies. METHODS: We detected ALK protein expression by immunohistochemistry and gene rearrangements by fluorescence in situ hybridisation in the ALKA-372-001 phase I study of the pan-Trk, ROS1, and ALK inhibitor entrectinib. One out of 487 CRCs showed ALK positivity with a peculiar pattern that prompted further characterisation by targeted sequencing using anchored multiplex PCR. RESULTS: A novel ALK fusion with the carbamoyl-phosphate synthetase 2, aspartate transcarbamylase, and dihydroorotase (CAD) gene (CAD-ALK fusion gene) was identified. It resulted from inversion within chromosome 2 and the fusion of exons 1-35 of CAD with exons 20-29 of ALK. After failure of previous standard therapies, treatment of this patient with the ALK inhibitor entrectinib resulted in a durable objective tumour response. CONCLUSIONS: We describe the novel CAD-ALK rearrangement as an oncogene and provide the first evidence of its drugability as a new molecular target in CRC.

Preface: BITS2014, the annual meeting of the Italian Society of Bioinformatics.

This Preface introduces the content of the BioMed Central journal Supplements related to BITS2014 meeting, held in Rome, Italy, from the 26th to the 28th of February, 2014.

The TPM3-NTRK1 rearrangement is a recurring event in colorectal carcinoma and is associated with tumor sensitivity to TRKA kinase inhibition.

The NTRK1 gene encodes Tropomyosin-related kinase A (TRKA), the high-affinity Nerve Growth Factor Receptor. NTRK1 was originally isolated from a colorectal carcinoma (CRC) sample as component of a somatic rearrangement (TPM3-NTRK1) resulting in expression of the oncogenic chimeric protein TPM3-TRKA, but there has been no subsequent report regarding the relevance of this oncogene in CRC. The KM12 human CRC cell line expresses the chimeric TPM3-TRKA protein and is hypersensitive to TRKA kinase inhibition. We report the detailed characterization of the TPM3-NTRK1 genomic rearrangement in KM12 cells and through a cellular screening approach, the identification of NMS-P626, a novel highly potent and selective TRKA inhibitor. NMS-P626 suppressed TPM3-TRKA phosphorylation and downstream signaling in KM12 cells and showed remarkable antitumor activity in mice bearing KM12 tumors. Finally, using quantitative reverse transcriptase PCR and immunohistochemistry (IHC) we identified the TPM3-NTRK1 rearrangement in a CRC clinical sample, therefore suggesting that this chromosomal translocation is indeed a low frequency recurring event in CRC and that such patients might benefit from therapy with TRKA kinase inhibitors.

Cell line identity finding by fingerprinting, an optimized resource for short tandem repeat profile authentication.

The generation of biological data on wide panels of tumor cell lines is recognized as a valid contribution to the cancer research community. However, research laboratories can benefit from this knowledge only after the identity of each individual cell line used in the experiments is verified and matched to external sources. Among the methods employed to assess cell line identity, DNA fingerprinting by profiling Short Tandem Repeat (STR) at variable loci has become the method of choice. However, the analysis of cancer cell lines is sometimes complicated by their intrinsic genetic instability, resulting in multiple allele calls per locus. In addition, comparison of data across different sources must deal with the heterogeneity of published profiles both in terms of number and type of loci used. The aim of this work is to provide the scientific community a homogeneous reference dataset for 300 widely used tumor cell lines, profiled in parallel on 16 loci. This large dataset is interfaced with an in-house developed software tool for Cell Line Identity Finding by Fingerprinting (CLIFF), featuring an original identity score calculation, which facilitates the comparison of STR profiles from different sources and enables accurate calls when multiple loci are present. CLIFF additionally allows import and query of proprietary STR profile datasets.

Transcriptional analysis of the Aurora inhibitor Danusertib leading to biomarker identification in TP53 wild type cells.

Aurora kinases represent an appealing target for anticancer therapies and several Aurora inhibitors are in clinical development, including the potent pan-Aurora inhibitor Danusertib. Treatment with Aurora inhibitors has been shown to induce diverse biological responses in different tumor cells, in part depending on TP53 status. To characterize the effects of Danusertib at the transcriptional level we carried out gene expression profiling of wt and TP53 mutant tumor cells showing differential cell cycle response upon drug treatment. We found that treatment with Danusertib induces a strong transcriptional response only in TP53 wt cells, with an overlapping pattern of expression of TP53-dependent genes among the three cell lines tested, while a prevalent signature could not be identified in the two TP53 mutant cells, suggesting that TP53 status is a key determinant for the observed transcriptional effects. This work led to the identification of a number of genes consistently modulated by Aurora treatment in TP53 cells. One of these is GDF15, a secreted protein belonging to the TGF-ß superfamily, for which we found a potential role in resistance to Danusertib, and which could represent a potential biomarker for Danusertib treatment in TP53 WT tumors and in surrogate tissues such as blood or skin.

Identification of candidate substrates for poly(ADP-ribose) polymerase-2 (PARP2) in the absence of DNA damage using high-density protein microarrays.

Poly(ADP-ribose) polymerase-2 (PARP2) belongs to the ADP-ribosyltransferase family of enzymes that catalyze the addition of ADP-ribose units to acceptor proteins, thus affecting many diverse cellular processes. In particular, PARP2 shares with PARP1 and, as recently highlighted, PARP3 the sole property of being catalytically activated by DNA-strand breaks, implying key downstream functions in the cellular response to DNA damage for both enzymes. However, evidence from several studies suggests unique functions for PARP2 in additional processes, possibly mediated through its basal, DNA-damage unstimulated ADP-ribosylating activity. Here, we describe the development and application of a protein microarray-based approach tailored to identify proteins that are ADP-ribosylated by PARP2 in the absence of DNA damage mimetics and might thus represent useful entry points to the exploration of novel PARP2 functions. Several candidate substrates for PARP2 were identified and global hit enrichment analysis showed a clear enrichment in translation initiation and RNA helicase molecular functions. In addition, the top scoring candidates FK506-binding protein 3 and SH3 and cysteine-rich domain-containing protein 1 were selected and confirmed in a complementary assay format as substrates for unstimulated PARP2.

Summarizing probe intensities of affymetrix GeneChip 3' expression arrays taking into account day-to-day variability.

Microarray experiments are affected by several sources of variability. The paper demonstrates the major role of the day-to-day variability, it underlines the importance of a randomized block design when processing replicates over several days to avoid systematic biases and it proposes a simple algorithm that minimizes the day dependence.

Abcg2 overexpression represents a novel mechanism for acquired resistance to the multi-kinase inhibitor Danusertib in BCR-ABL-positive cells in vitro.

The success of Imatinib (IM) therapy in chronic myeloid leukemia (CML) is compromised by the development of IM resistance and by a limited IM effect on hematopoietic stem cells. Danusertib (formerly PHA-739358) is a potent pan-aurora and ABL kinase inhibitor with activity against known BCR-ABL mutations, including T315I. Here, the individual contribution of both signaling pathways to the therapeutic effect of Danusertib as well as mechanisms underlying the development of resistance and, as a consequence, strategies to overcome resistance to Danusertib were investigated. Starting at low concentrations, a dose-dependent inhibition of BCR-ABL activity was observed, whereas inhibition of aurora kinase activity required higher concentrations, pointing to a therapeutic window between the two effects. Interestingly, the emergence of resistant clones during Danusertib exposure in vitro occurred considerably less frequently than with comparable concentrations of IM. In addition, Danusertib-resistant clones had no mutations in BCR-ABL or aurora kinase domains and remained IM-sensitive. Overexpression of Abcg2 efflux transporter was identified and functionally validated as the predominant mechanism of acquired Danusertib resistance in vitro. Finally, the combined treatment with IM and Danusertib significantly reduced the emergence of drug resistance in vitro, raising hope that this drug combination may also achieve more durable disease control in vivo.

Discovery of drug mode of action and drug repositioning from transcriptional responses.

A bottleneck in drug discovery is the identification of the molecular targets of a compound (mode of action, MoA) and of its off-target effects. Previous approaches to elucidate drug MoA include analysis of chemical structures, transcriptional responses following treatment, and text mining. Methods based on transcriptional responses require the least amount of information and can be quickly applied to new compounds. Available methods are inefficient and are not able to support network pharmacology. We developed an automatic and robust approach that exploits similarity in gene expression profiles following drug treatment, across multiple cell lines and dosages, to predict similarities in drug effect and MoA. We constructed a "drug network" of 1,302 nodes (drugs) and 41,047 edges (indicating similarities between pair of drugs). We applied network theory, partitioning drugs into groups of densely interconnected nodes (i.e., communities). These communities are significantly enriched for compounds with similar MoA, or acting on the same pathway, and can be used to identify the compound-targeted biological pathways. New compounds can be integrated into the network to predict their therapeutic and off-target effects. Using this network, we correctly predicted the MoA for nine anticancer compounds, and we were able to discover an unreported effect for a well-known drug. We verified an unexpected similarity between cyclin-dependent kinase 2 inhibitors and Topoisomerase inhibitors. We discovered that Fasudil (a Rho-kinase inhibitor) might be "repositioned" as an enhancer of cellular autophagy, potentially applicable to several neurodegenerative disorders. Our approach was implemented in a tool (Mode of Action by NeTwoRk Analysis, MANTRA, http://mantra.tigem.it).