The AACR Project GENIE is an international data-sharing consortium focused on generating an evidence base for precision cancer medicine by integrating clinical-grade cancer genomic data with clinical outcome data for tens of thousands of cancer patients treated at multiple institutions worldwide. In conjunction with the first public data release from approximately 19,000 samples, we describe the goals, structure, and data standards of the consortium and report conclusions from high-level analysis of the initial phase of genomic data. We also provide examples of the clinical utility of GENIE data, such as an estimate of clinical actionability across multiple cancer types (>30%) and prediction of accrual rates to the NCI-MATCH trial that accurately reflect recently reported actual match rates. The GENIE database is expected to grow to >100,000 samples within 5 years and should serve as a powerful tool for precision cancer medicine. Significance The AACR Project GENIE aims to catalyze sharing of integrated genomic and clinical datasets across multiple institutions worldwide, and thereby enable precision cancer medicine research, including the identification of novel therapeutic targets, design of biomarker-driven clinical trials, and identification of genomic determinants of response to therapy.

Mucormycosis is a life-threatening infection caused by Mucorales fungi. Here we sequence 30 fungal genomes, and perform transcriptomics with three representative Rhizopus and Mucor strains and with human airway epithelial cells during fungal invasion, to reveal key host and fungal determinants contributing to pathogenesis. Analysis of the host transcriptional response to Mucorales reveals platelet-derived growth factor receptor B (PDGFRB) signaling as part of a core response to divergent pathogenic fungi; inhibition of PDGFRB reduces Mucorales-induced damage to host cells. The unique presence of CotH invasins in all invasive Mucorales, and the correlation between CotH gene copy number and clinical prevalence, are consistent with an important role for these proteins in mucormycosis pathogenesis. Our work provides insight into the evolution of this medically and economically important group of fungi, and identifies several molecular pathways that might be exploited as potential therapeutic targets.

PIWI-interacting RNAs (piRNAs) are thought to silence transposon and gene expression during development. However, the roles of piRNAs in somatic tissues are largely unknown. Here we report the identification of 555 piRNAs in human lung bronchial epithelial (HBE) and non-small cell lung cancer (NSCLC) cell lines, including 295 that do not exist in databases termed as piRNA-like sncRNAs or piRNA-Ls. Distinctive piRNA/piRNA-L expression patterns are observed between HBE and NSCLC cells. piRNA-like-163 (piR-L-163), the top downregulated piRNA-L in NSCLC cells, binds directly to phosphorylated ERM proteins (p-ERM), which is dependent on the central part of UUNNUUUNNUU motif in piR-L-163 and the RRRKPDT element in ERM. The piR-L-163/p-ERM interaction is critical for p-ERM's binding capability to filamentous actin (F-actin) and ERM-binding phosphoprotein 50 (EBP50). Thus, piRNA/piRNA-L may play a regulatory role through direct interaction with proteins in physiological and pathophysiological conditions.

Babesia microti, a tick-transmitted, intraerythrocytic protozoan parasite circulating mainly among small mammals, is the primary cause of human babesiosis. While most cases are transmitted by Ixodes ticks, the disease may also be transmitted through blood transfusion and perinatally. A comprehensive analysis of genome composition, genetic diversity, and gene expression profiling of seven B. microti isolates revealed that genetic variation in isolates from the Northeast United States is almost exclusively associated with genes encoding the surface proteome and secretome of the parasite. Furthermore, we found that polymorphism is restricted to a small number of genes, which are highly expressed during infection. In order to identify pathogen-encoded factors involved in host-parasite interactions, we screened a proteome array comprised of 174 B. microti proteins, including several predicted members of the parasite secretome. Using this immuno-proteomic approach we identified several novel antigens that trigger strong host immune responses during the onset of infection. The genomic and immunological data presented herein provide the first insights into the determinants of B. microti interaction with its mammalian hosts and their relevance for understanding the selective pressures acting on parasite evolution.

Candida albicans, the major invasive fungal pathogen of humans, can cause both debilitating mucosal infections and fatal invasive infections. Understanding the complex nature of the host-pathogen interaction in each of these contexts is essential to developing desperately needed therapies to treat fungal infections. RNA-seq enables a systems-level understanding of infection by facilitating comprehensive analysis of transcriptomes from multiple species (e.g., host and pathogen) simultaneously. We used RNA-seq to characterize the transcriptomes of both C. albicans and human endothelial cells or oral epithelial cells during in vitro infection. Network analysis of the differentially expressed genes identified the activation of several signaling pathways that have not previously been associated with the host response to fungal pathogens. Using an siRNA knockdown approach, we demonstrate that two of these pathways-platelet-derived growth factor BB (PDGF BB) and neural precursor-cell-expressed developmentally down-regulated protein 9 (NEDD9)-govern the host-pathogen interaction by regulating the uptake of C. albicans by host cells. Using RNA-seq analysis of a mouse model of hematogenously disseminated candidiasis (HDC) and episodes of vulvovaginal candidiasis (VVC) in humans, we found evidence that many of the same signaling pathways are activated during mucosal (VVC) and/or disseminated (HDC) infections in vivo. Our analyses have uncovered several signaling pathways at the interface between C. albicans and host cells in various contexts of infection, and suggest that PDGF BB and NEDD9 play important roles in this interaction. In addition, these data provide a valuable community resource for better understanding host-fungal pathogen interactions.

BackgroundDrosophila melanogaster activates a variety of immune responses against microbial infections. However, information on the Drosophila immune response to entomopathogenic nematode infections is currently limited. The nematode Heterorhabditis bacteriophora is an insect parasite that forms a mutualistic relationship with the gram-negative bacteria Photorhabdus luminescens. Following infection, the nematodes release the bacteria that quickly multiply within the insect and produce several toxins that eventually kill the host. Although we currently know that the insect immune system interacts with Photorhabdus, information on interaction with the nematode vector is scarce.ResultsHere we have used next generation RNA-sequencing to analyze the transcriptional profile of wild-type adult flies infected by axenic Heterorhabditis nematodes (lacking Photorhabdus bacteria), symbiotic Heterorhabditis nematodes (carrying Photorhabdus bacteria), and Photorhabdus bacteria alone. We have obtained approximately 54 million reads from the different infection treatments. Bioinformatic analysis shows that infection with Photorhabdus alters the transcription of a large number of Drosophila genes involved in translational repression as well in response to stress. However, Heterorhabditis infection alters the transcription of several genes that participate in lipidhomeostasis and metabolism, stress responses, DNA/protein sythesis and neuronal functions. We have also identified genes in the fly with potential roles in nematode recognition, anti-nematode activity and nociception.ConclusionsThese findings provide fundamental information on the molecular events that take place in Drosophila upon infection with the two pathogens, either separately or together. Such large-scale transcriptomic analyses set the stage for future functional studies aimed at identifying the exact role of key factors in the Drosophila immune response against nematode-bacteria complexes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1690-2) contains supplementary material, which is available to authorized users.

Background and objectives Haemoglobin content is the well accepted indicator for anaemia assessment. The high prevalence of anaemia, maternal health care issues and adverse delivery outcome in Jharkhand, we investigated whether delivering women with anaemia would present a modifiable risk of preterm (PTB) and low birth weight (LBW). Methods A facility-based cross-sectional study involving pregnant women, with screening for pregnancy endpoints and haemoglobin assay, were conducted. Anaemia was classified according to World Health Organization's definition of anaemia in pregnancy. Confounding variables were adjusted in a logistic model. The adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were used for analyzing the association among maternal anaemia, PTB and LBW. Results We observed a high prevalence of anaemia (78.45%) in delivering women, whereas high prevalence of preterm birth (34.75%) and LBW (32.81%) in delivering women overall. In the adjusted analysis, overall anaemia in pregnancy was strongly associated with preterm birth (OR, 3.42; 95% CI, 1.98–5.88; P ≤ .0001 ) as compared to LBW (OR, 1.12; 95% CI, 0.65–1.61; P = .0003 ). The risk of PTB and LBW were dependent on the stratification of the anaemia group, as the strongest association was observed in severe (OR, 4.86) followed by mild (OR, 3.66) and moderate (OR, 3.18) anaemia in PTB; whereas risk of LBW was found in severe (OR, 2.5) followed by moderate (OR, 1.11) and mild (OR, 0.57) anaemia. The risk of PTB and LBW across six pregnancy haemoglobin groups were compared, haemoglobin of 10–10.9 g/dl (OR, 1.25) and ≤ 8 g/dl (OR, 1.03) have shown association with PTB and LBW, respectively. However, high haemoglobin concentration was not associated with either PTB or LBW. Conclusions Anaemia in delivering women was associated with an elevated risk of PTB and LBW and the risk increased with the severity of anaemia in pregnant women.

PURPOSE Cancer classification is foundational for patient care and oncology research. Systems such as International Classification of Diseases for Oncology (ICD-O), Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT), and National Cancer Institute Thesaurus (NCIt) provide large sets of cancer classification terminologies but they lack a dynamic modernized cancer classification platform that addresses the fast-evolving needs in clinical reporting of genomic sequencing results and associated oncology research. METHODS To meet these needs, we have developed OncoTree, an open-source cancer classification system. It is maintained by a cross-institutional committee of oncologists, pathologists, scientists, and engineers, accessible via an open-source Web user interface and an application programming interface. RESULTS OncoTree currently includes 868 tumor types across 32 organ sites. OncoTree has been adopted as the tumor classification system for American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE), a large genomic and clinical data-sharing consortium, and for clinical molecular testing efforts at Memorial Sloan Kettering Cancer Center and Dana-Farber Cancer Institute. It is also used by precision oncology tools such as OncoKB and cBioPortal for Cancer Genomics. CONCLUSION OncoTree is a dynamic and flexible community-driven cancer classification platform encompassing rare and common cancers that provides clinically relevant and appropriately granular cancer classification for clinical decision support systems and oncology research.