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Background Lung NET, classified in typical carcinoids (TC) and atypical carcinoids (AC), are highly heterogeneous in their biology and prognosis. The histological subtype and TNM stage are well-established prognostic factors for lung NET. In a previous work by our group, we demonstrated a significant impact of laterality on lung NET survival outcomes. Materials and methods We developed a nomogram that integrates relevant prognostic factors to predict lung NET outcomes. By adding the scores for each of the variables included in the model, it was possible to obtain a prognostic score (Rachel score). Wilcoxon non-parametric statistical test was applied among parameters and Harrell’s concordance index was used to measure the models’ predictive power. To test the discriminatory power and the predictive accuracy of the model, we calculated Gonen and Heller concordance index. Time-dependent ROC curves and their area under the curve (AUC) were used to evaluate the models’ predictive performance. Results By applying Rachel score, we were able to identify three prognostic groups (specifically, high, medium and low risk). These three groups were associate to well-defined ranges of points according to the obtained nomogram (I: 0–90, II: 91–130; III: > 130 points), providing a useful tool for prognostic stratification. The overall survival (OS) and progression free survival (PFS) Kaplan–Meier curves confirmed significant differences ( p < 0.0001) among the three groups identified by Rachel score. Conclusions A prognostic nomogram was developed, incorporating variables with significant impact on lung NET survival. The nomogram showed a satisfactory and stable ability to predict OS and PFS in this population, confirming the heterogeneity beyond the histopathological diagnosis of TC vs AC.

The tumor suppressor p53 is mainly involved in the transcriptional regulation of a large number of growth-arrest- and apoptosis-related genes. However, a clear understanding of which factor/s influences the choice between these two opposing p53-dependent outcomes remains largely elusive. We have previously described that in response to DNA damage, the RNA polymerase II-binding protein Che-1/AATF transcriptionally activates p53. Here, we show that Che-1 binds directly to p53. This interaction essentially occurs in the first hours of DNA damage, whereas it is lost when cells undergo apoptosis in response to posttranscriptional modifications. Moreover, Che-1 sits in a ternary complex with p53 and the oncosuppressor Brca1. Accordingly, our analysis of genome-wide chromatin occupancy by p53 revealed that p53/Che1 interaction results in preferential transactivation of growth arrest p53 target genes over its pro-apoptotic target genes. Notably, exposure of Che-1 +/− mice to ionizing radiations resulted in enhanced apoptosis of thymocytes, compared with WT mice. These results confirm Che-1 as an important regulator of p53 activity and suggest Che-1 to be a promising yet attractive drug target for cancer therapy.

Developmental toxicity in vitro assays have hitherto been established as stand-alone systems, based on a limited number of toxicants. Within the embryonic stem cell-based novel alternative tests project, we developed a test battery framework that allows inclusion of any developmental toxicity assay and that explores the responses of such test systems to a wide range of drug-like compounds. We selected 28 compounds, including several biologics (e.g., erythropoietin), classical pharmaceuticals (e.g., roflumilast) and also six environmental toxicants. The chemical, toxicological and clinical data of this screen library were compiled. In order to determine a non-cytotoxic concentration range, cytotoxicity data were obtained for all compounds from HEK293 cells and from murine embryonic stem cells. Moreover, an estimate of relevant exposures was provided by literature data mining. To evaluate feasibility of the suggested test framework, we selected a well-characterized assay that evaluates ‘migration inhibition of neural crest cells.’ Screening at the highest non-cytotoxic concentration resulted in 11 hits (e.g., geldanamycin, abiraterone, gefitinib, chlorpromazine, cyproconazole, arsenite). These were confirmed in concentration–response studies. Subsequent pharmacokinetic modeling indicated that triadimefon exerted its effects at concentrations relevant to the in vivo situation, and also interferon-β and polybrominated diphenyl ether showed effects within the same order of magnitude of concentrations that may be reached in humans. In conclusion, the test battery framework can identify compounds that disturb processes relevant for human development and therefore may represent developmental toxicants. The open structure of the strategy allows rich information to be generated on both the underlying library, and on any contributing assay.

Hazard assessment, based on new approach methods (NAM), requires the use of batteries of assays, where individual tests may be contributed by different laboratories. A unified strategy for such collaborative testing is presented. It details all procedures required to allow test information to be usable for integrated hazard assessment, strategic project decisions and/or for regulatory purposes. The EU-ToxRisk project developed a strategy to provide regulatorily valid data, and exemplified this using a panel of > 20 assays (with > 50 individual endpoints), each exposed to 19 well-known test compounds (e.g. rotenone, colchicine, mercury, paracetamol, rifampicine, paraquat, taxol). Examples of strategy implementation are provided for all aspects required to ensure data validity: (i) documentation of test methods in a publicly accessible database; (ii) deposition of standard operating procedures (SOP) at the European Union DB-ALM repository; (iii) test readiness scoring accoding to defined criteria; (iv) disclosure of the pipeline for data processing; (v) link of uncertainty measures and metadata to the data; (vi) definition of test chemicals, their handling and their behavior in test media; (vii) specification of the test purpose and overall evaluation plans. Moreover, data generation was exemplified by providing results from 25 reporter assays. A complete evaluation of the entire test battery will be described elsewhere. A major learning from the retrospective analysis of this large testing project was the need for thorough definitions of the above strategy aspects, ideally in form of a study pre-registration, to allow adequate interpretation of the data and to ensure overall scientific/toxicological validity.

BackgroundImmune checkpoint inhibitors (ICIs) provide significant survival benefits in non-small cell lung cancer (NSCLC). Nevertheless, while some patients obtain a prolonged benefit, a non-negligible fraction of patients experiences an ultrarapid disease progression. Identifying specific molecular backgrounds predicting opposite outcomes is instrumental to optimize the use of these agents in clinical practice.MethodsWe carried out an observational study with prospective design envisioning targeted next-generation sequencing (NGS) with an approved assay in 55 patients with metastatic NSCLC (Rome cohort), of whom 35 were treated with ICIs. Data from three clinically comparable datasets were collected and combined into a metadataset containing 779 patients. The datasets were related to the Memorial Sloan Kettering Cancer Center (MSKCC) cohort (tissue-based NGS) and the randomized phase II and III POPLAR and OAK trials (blood-based NGS).ResultsIn patients treated with ICIs in the Rome cohort, co-occurring mutations in NOTCH1-3 and homologous repair (HR) genes were associated with durable clinical benefit. Using the MSKCC/POPLAR/OAK metadaset, we confirmed the relationship between the NOTCHmut/HRmut signature and longer progression-free survival (PFS) in ICI-treated patients (multivariate Cox: HR 0.51, 95% CI 0.34 to 0.76, p=0.001). The NOTCHmut/HRmut genomic predictor was also associated with longer survival (log-rank p=0.008), despite patients whose tumors carried the NOTCHmut/HRmut signature had higher metastatic burden as compared with their negative counterpart. Finally, we observed that this genomic predictor was also associated with longer survival in patients with other tumor types treated with ICIs (n=1311, log-rank p=0.002).ConclusionsCo-occurring mutations in the NOTCH and HR pathways are associated with increased efficacy of immunotherapy in advanced NSCLC. This genomic predictor deserves further investigation to fully assess its potential in informing therapeutic decisions.