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[Image: see text] Poly(ADP-ribose) polymerase-1 (PARP-1) is an enzyme involved in signaling and repair of DNA single strand breaks. PARP-1 employs NAD(+) to modify substrate proteins via the attachment of poly(ADP-ribose) chains. PARP-1 is a well established target in oncology, as testified by the number of marketed drugs (e.g., Lynparza, Rubraca, Zejula, and Talzenna) used for the treatment of ovarian, breast, and prostate tumors. Efforts in investigating an uncharted region of the previously identified isoindolinone carboxamide series delivered (S)-13 (NMS-P515), a potent inhibitor of PARP-1 both in biochemical (K(d): 0.016 μM) and cellular (IC(50): 0.027 μM) assays. Cocrystal structure allowed explaining NMS-P515 stereospecific inhibition of the target. After having ruled out potential loss of enantiopurity in vitro and in vivo, NMS-P515 was synthesized in an asymmetric fashion. NMS-P515 ADME profile and its antitumor activity in a mouse xenograft cancer model render the compound eligible for further optimization.

Cancer cells within a tumour have heterogeneous phenotypes and exhibit dynamic plasticity. How to evaluate such heterogeneity and its impact on outcome and drug response is still unclear. Here, we transcriptionally profile 35,276 individual cells from 32 breast cancer cell lines to yield a single cell atlas. We find high degree of heterogeneity in the expression of biomarkers. We then train a deconvolution algorithm on the atlas to determine cell line composition from bulk gene expression profiles of tumour biopsies, thus enabling cell line-based patient stratification. Finally, we link results from large-scale in vitro drug screening in cell lines to the single cell data to computationally predict drug responses starting from single-cell profiles. We find that transcriptional heterogeneity enables cells with differential drug sensitivity to co-exist in the same population. Our work provides a framework to determine tumour heterogeneity in terms of cell line composition and drug response.

Binary (nucleotide-protein dimer and hexamer complexes) and ternary (nucleotide-protein-inhibitor complexes) p97 complexes were subjected to molecular dynamics simulations in an attempt to further our understanding of the p97 protein oligomer domain stability and, more importantly, of the recently reported diverse molecular mechanisms of inhibition including allosteric, ATP-competitive and covalent inhibitors. Analysis of stable states following equilibration phases indicated a higher intrinsic stability of the homohexamer as opposed to the dimer, and of N-D1 domains as opposed to the D2 domain. The molecular dynamics of the proposed allosteric binding model reproduced important molecular interactions identified experimentally with high frequency throughout the trajectory. Observed conformational changes occurring in the D2 nucleotide binding site provided a novel bind-rearrange-react hypothesis of stepwise molecular events involved in the specific covalent inhibitor mode of action.

Breast cancer patient stratification is mainly driven by tumour receptor status and histological grading and subtyping, with about twenty percent of patients for which absence of any actionable biomarkers results in no clear therapeutic intervention. Cancer cells within the same tumour have heterogeneous phenotypes and exhibit dynamic plasticity. However, how to evaluate such heterogeneity and its impact on outcome and drug response is still unclear. Here, we transcriptionally profiled 35,276 individual cells from 32 breast cancer cell lines covering all main breast cancer subtypes to yield a breast cancer cell line atlas. We found high degree of heterogeneity in the expression of clinically relevant biomarkers across individual cells within the same cell line; such heterogeneity is non-genetic and dynamic. We computationally mapped single cell transcriptional profiles of patients’ tumour biopsies to the atlas to determine their composition in terms of cell lines. Each tumour was found to be heterogenous and composed of multiple cell lines mostly, but not exclusively, of the same subtype. We then trained an algorithm on the atlas to determine cell line composition from bulk gene expression profiles of tumour biopsies, thus providing a novel approach to patient stratification. Finally, we linked results from large-scale in vitro drug screening1,2to the single cell data to computationally predict responses to more than 450 anticancer agents starting from single-cell transcriptional profiles. We thus found that transcriptional heterogeneity enables cells with differential drug sensitivity to co-exist in the same population. Our work provides a unique resource and a novel framework to determine tumour heterogeneity and drug response in breast cancer patients.

La presente analisi di congiuntura prende come riferimento il periodo da marzo ad ottobre, caratterizzato da diverse fasi dell’emergenza Covid, esaminando il vissuto di alcuni servizi diurni, residenziali e semiresidenziali, presenti nella provincia di Roma e Viterbo (distretto VT5), in particolare Capena, Monterotondo e Civita Castellana. Per analizzare la I e II fase del lockdown, da marzo a maggio, è necessario fare riferimento agli articoli 47 e 48 introdotti dal decreto Cura Italia, approvato il 16 marzo 2020 e pubblicato in Gazzetta Ufficiale il 17 marzo 2020. Tale decreto pone l’accento sulle principali misure previste per le famiglie di persone con disabilità che prevedono congedi parentali, aumento di permessi lavorativi da legge 104, lavoro agevole, sospensione e rimodulazione dei centri semiresidenziali a carattere socio-assistenziale, socio-educativo, polifunzionale, socio-occupazionale, sanitario e socio-sanitario e rimodulazione dei servizi da parte delle pubbliche amministrazioni in forma domiciliare o a distanza. Mentre nella II fase è importante fare riferimento al dpcm del 26 aprile 2020, in cui sono previste prudenti aperture rispetto al lockdown a partire dal 4 maggio 2020. In particolare nelle specifiche previste per le persone con disabilità, sono consentite le riaperture dei servizi semiresidenziali, secondo i piani territoriali regionali e l’attivazione di specifici protocolli necessari per la prevenzione del contagio e la tutela della salute delle persone.

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.

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, PDGFRβ, 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 PDGFRβ 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.

In this article we describe the identification of unprecedented ATP-competitive ChoKα inhibitors starting from initial hit NMS-P830 that binds to ChoKα in an ATP concentration-dependent manner. This result is confirmed by the co-crystal structure of NMS-P830 in complex with Δ75-ChoKα. NMS-P830 is able to inhibit ChoKα in cells resulting in the reduction of intracellular phosphocholine formation. A structure-based medicinal chemistry program resulted in the identification of selective compounds that have good biochemical activity, solubility and metabolic stability and are suitable for further optimization. The ChoKα inhibitors disclosed in this article demonstrate for the first time the possibility to inhibit ChoKα with ATP-competitive compounds.

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.

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.

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.