Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

In summary, our meta-analysis suggested that a definitive conclusion could not be reached regarding which surgical approach is more effective for the treatment of multilevel CSM. Although anterior approach was associated with better postoperative neural function than posterior approach in the treatment of multilevel CSM, there was no apparent difference in the neural function recovery rate between the two approaches. Higher rates of surgery-related complication and reoperation should be taken into consideration when anterior approach is used for patients with multilevel CSM.

Summary Although non-small cell lung cancer (NSCLC) patients benefit from standard taxane-platin chemotherapy, many relapse, developing drug resistance. We established preclinical taxane-platin chemoresistance models and identified a 35-gene resistance signature, which associated with poor recurrence-free survival in neoadjuvant-treated NSCLC patients and included upregulation of the JumonjiC lysine demethylase KDM3B. In fact, multi-drug resistant cells progressively increased expression of many JumonjiC demethylases, had altered histone methylation and importantly showed hypersensitivity to JumonjiC inhibitors, in vitro and in vivo. Increasing taxane-platin resistance in progressive cell line series was accompanied by progressive sensitization to JIB-04 and GSK-J4. These JumonjiC inhibitors partly reversed deregulated transcriptional programs, prevented the emergence of drug-tolerant colonies from chemo-naïve cells and synergized with standard chemotherapy in vitro and in vivo. Our findings reveal JumonjiC inhibitors as promising therapies for targeting taxane-platin chemoresistant NSCLCs.

The ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000-Genomes Project. The challenge participants developed algorithms to predict inter-individual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against a blinded experimental dataset. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson’s r<0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r<0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal.

Numerous environmental factors influence isoflavone accumulation and have long hampered their genetic dissection. Temperature and water regimes are two of the most significant abiotic factors. However, while the effects of temperature have been widely studied, little is known about how water scarcity might affect isoflavone concentration in seeds. Studies have shown that accumulation of isoflavones is promoted by well-watered conditions, but the molecular basis remains elusive. The length and severity of the water stress required to induce changes are also still unknown. In the present work, several intensities of water stress were evaluated at various critical stages for soybean [Glycine max (L.) Merr.] seed development, in both field and controlled environments. The results suggested that only long-term progressive drought, spanning most of the seed developmental stages, significantly decreased isoflavone content in seeds. The reduction is proportional to the intensity of the stress and appears to occur in a genotype-dependent manner. However, regardless of water regime, isoflavone compounds were mainly accumulated in the later seed developmental stages. Transcripts of the most important genes for isoflavone biosynthesis were also quantified from samples collected at key seed developmental stages under well-watered and long-term water deficit conditions. Expression of CHS7, CHS8 and IFS2 correlated with isoflavone accumulation under well-watered conditions. Interestingly, we found that the two isoflavone synthase genes in soybean (IFS1 and IFS2) showed different patterns of expression. The abundance of IFS1 transcripts was maintained at a constant rate, whereas IFS2 was down-regulated and highly correlated with isoflavone accumulation under both water deficit and well-watered conditions, suggesting IFS2 as a main contributor to isoflavone diminution under drought.