Purpose: Small-cell lung cancer (SCLC) has been treated clinically as a homogeneous disease, but recent discoveries suggest that SCLC is heterogeneous. Whether metabolic differences exist among SCLC subtypes is largely unexplored. In this study, we aimed to determine whether metabolic vulnerabilities exist between SCLC subtypes that can be therapeutically exploited.Experimental Design: We performed steady state metabolomics on tumors isolated from distinct genetically engineered mouse models (GEMM) representing the MYC-and MYCLdriven subtypes of SCLC. Using genetic and pharmacologic approaches, we validated our findings in chemo-na€ ve and -resistant human SCLC cell lines, multiple GEMMs, four human cell line xenografts, and four newly derived PDX models.Results: We discover that SCLC subtypes driven by different MYC family members have distinct metabolic pro-files. MYC-driven SCLC preferentially depends on arginineregulated pathways including polyamine biosynthesis and mTOR pathway activation. Chemo-resistant SCLC cells exhibit increased MYC expression and similar metabolic liabilities as chemo-na€ ve MYC-driven cells. Arginine depletion with pegylated arginine deiminase (ADI-PEG 20) dramatically suppresses tumor growth and promotes survival of mice specifically with MYC-driven tumors, including in GEMMs, human cell line xenografts, and a patient-derived xenograft from a relapsed patient. Finally, ADI-PEG 20 is significantly more effective than the standard-of-care chemotherapy.Conclusions: These data identify metabolic heterogeneity within SCLC and suggest arginine deprivation as a subtype-specific therapeutic vulnerability for MYC-driven SCLC. DiscussionDespite numerous clinical trials and years of research, therapeutic options for SCLC remain limited. However, recent studies suggest that molecular subtypes of SCLC exist with distinct

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Pentatricopeptide repeat (PPR) proteins are the largest known RNA-binding protein family, and are found in all eukaryotes, being particularly abundant in higher plants. PPR proteins localize mostly to mitochondria and chloroplasts, and many were shown to modulate organellar genome expression on the posttranscriptional level. Although the genomes of land plants encode hundreds of PPR proteins, only a few have been identified in Fungi and Metazoa. As the current PPR motif profiles are built mainly on the basis of the predominant plant sequences, they are unlikely to be optimal for detecting fungal and animal members of the family, and many putative PPR proteins in these genomes may remain undetected. In order to verify this hypothesis, we designed a hidden Markov model-based bioinformatic tool called Supervised Clustering-based Iterative Phylogenetic Hidden Markov Model algorithm for the Evaluation of tandem Repeat motif families (SCIPHER) using sequence data from orthologous clusters from available yeast genomes. This approach allowed us to assign 12 new proteins in Saccharomyces cerevisiae to the PPR family. Similarly, in other yeast species, we obtained a 5-fold increase in the detection of PPR motifs, compared with the previous tools. All the newly identified S. cerevisiae PPR proteins localize in the mitochondrion and are a part of the RNA processing interaction network. Furthermore, the yeast PPR proteins seem to undergo an accelerated divergent evolution. Analysis of single and double amino acid substitutions in the Dmr1 protein of S. cerevisiae suggests that cooperative interactions between motifs and pseudoreversion could be the force driving this rapid evolution.

ObjectiveTo evaluate the performance of diagnostic prediction models for ovarian malignancy in all patients with an ovarian mass managed surgically or conservatively.DesignMulticentre cohort study.Setting36 oncology referral centres (tertiary centres with a specific gynaecological oncology unit) or other types of centre.ParticipantsConsecutive adult patients presenting with an adnexal mass between January 2012 and March 2015 and managed by surgery or follow-up.Main outcome measuresOverall and centre specific discrimination, calibration, and clinical utility of six prediction models for ovarian malignancy (risk of malignancy index (RMI), logistic regression model 2 (LR2), simple rules, simple rules risk model (SRRisk), assessment of different neoplasias in the adnexa (ADNEX) with or without CA125). ADNEX allows the risk of malignancy to be subdivided into risks of a borderline, stage I primary, stage II-IV primary, or secondary metastatic malignancy. The outcome was based on histology if patients underwent surgery, or on results of clinical and ultrasound follow-up at 12 (±2) months. Multiple imputation was used when outcome based on follow-up was uncertain.ResultsThe primary analysis included 17 centres that met strict quality criteria for surgical and follow-up data (5717 of all 8519 patients). 812 patients (14%) had a mass that was already in follow-up at study recruitment, therefore 4905 patients were included in the statistical analysis. The outcome was benign in 3441 (70%) patients and malignant in 978 (20%). Uncertain outcomes (486, 10%) were most often explained by limited follow-up information. The overall area under the receiver operating characteristic curve was highest for ADNEX with CA125 (0.94, 95% confidence interval 0.92 to 0.96), ADNEX without CA125 (0.94, 0.91 to 0.95) and SRRisk (0.94, 0.91 to 0.95), and lowest for RMI (0.89, 0.85 to 0.92). Calibration varied among centres for all models, however the ADNEX models and SRRisk were the best calibrated. Calibration of the estimated risks for the tumour subtypes was good for ADNEX irrespective of whether or not CA125 was included as a predictor. Overall clinical utility (net benefit) was highest for the ADNEX models and SRRisk, and lowest for RMI. For patients who received at least one follow-up scan (n=1958), overall area under the receiver operating characteristic curve ranged from 0.76 (95% confidence interval 0.66 to 0.84) for RMI to 0.89 (0.81 to 0.94) for ADNEX with CA125.ConclusionsOur study found the ADNEX models and SRRisk are the best models to distinguish between benign and malignant masses in all patients presenting with an adnexal mass, including those managed conservatively.Trial registrationClinicalTrials.gov NCT01698632.

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