Cancer Moonshot Data and Technology Team: Enabling a National Learning Healthcare System for Cancer to Unleash the Power of Data.

The Cancer Moonshot emphasizes the need to learn from the experiences of cancer patients to positively impact their outcomes, experiences, and qualities of life. To realize this vision, there has been a concerted effort to identify the fundamental building blocks required to establish a National Learning Healthcare System for Cancer, such that relevant data on all cancer patients is accessible, shareable, and contributing to the current state of knowledge of cancer care and outcomes.

Gene Ontology annotations and resources.

The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources.

The Gene Ontology (GO) database and informatics resource.

The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the annotation of genes, gene products and sequences. Many model organism databases and genome annotation groups use the GO and contribute their annotation sets to the GO resource. The GO database integrates the vocabularies and contributed annotations and provides full access to this information in several formats. Members of the GO Consortium continually work collectively, involving outside experts as needed, to expand and update the GO vocabularies. The GO Web resource also provides access to extensive documentation about the GO project and links to applications that use GO data for functional analyses.

An assessment of cancer clinical trials vocabulary and IT infrastructure in the U.S.

Twenty-three cancer research centers in the U.S. were assessed to determine data standards, vocabularies, and information infrastructure used in support of clinical trials. Eighteen of the 23 responded. Major findings were related to: 1) clinical trials infrastructure information, 2) current systems environment, 3) technical details, and 4) vocabulary and data standards. The size of the facility correlated with the quality, features and functionality of the clinical trials system (CTS). One facility had as many as 22 separate CTS. There were only 2 sites that had integrated clinical information systems (CIS) with CTS. The responses included the major vocabularies and data standards used in CTS. The majority used some automation but many also reported manual data entry. CTS had more manual entry than CIS because of regulatory reporting requirements. The assessment identified opportunities for guidance in defining vocabularies and standards for cancer clinical trial systems in the US.

The SV40 core sequence functions as a repressor element in yeast.

Our previous studies showed that the AP-1 recognition element (ARE) present within the SV40 72-base pair (bp) enhancer will activate transcription in yeast when placed upstream of a truncated CYC1 promoter. However, the AP-2/AP-3 recognition element (also known as the core sequence TGTGGAAAG) from the SV40 enhancer was not able to activate CYC1-dependent transcription. In this report, we show that the core sequence, when cloned next to a yeast UAS (upstream activation sequence), can inhibit the transcriptional stimulatory activity of the UAS. We refer to this sequence as the upstream repressor element (URE) in yeast. Repression occurs in an orientation-independent fashion and irrespective of the placement of the URE between the UAS and TATA box or upstream of both of these elements. Furthermore, repression is seen when the URE is separated from the UAS by up to 214 bp. Interestingly, multiple copies of an activator site can overcome this repression. Gel-shift analysis and URE-probed proteins blots indicate the presence of two polypeptide chains capable of binding the URE in yeast. The experimental evidence suggests that either the repression associated with the URE sequence is mediated by a direct, one-to-one interaction between the proteins recognizing the URE and GCRE, or alternatively, that there is a direct interaction between the activator and repressor for a general transcription factor.

The Saccharomyces and Drosophila heat shock transcription factors are identical in size and DNA binding properties.

The heat shock transcription factor (HSTF) has been purified to apparent homogeneity from S. cerevisiae and D. melanogaster by sequence-specific DNA-affinity chromatography. A synthetic oligonucleotide containing an hsp83-like heat shock element (HSE) was prepared and ligated into concatamers and covalently coupled to Sepharose. This DNA-affinity resin allowed the rapid isolation of a yeast and a Drosophila protein with the same apparent molecular weight (70 kd). The yeast HSTF will bind to both its own and the Drosophila HSEs. Similarly, the Drosophila HSTF will bind to both its own and the yeast HSEs. The yeast and Drosophila HSTFs were subjected to preparative SDS gel electrophoresis, and the 70 kd polypeptides were eluted, renatured, and observed to generate the identical footprint pattern as the native HSTFs. Affinity-purified Drosophila HSTF was further shown to stimulate specific HSE-dependent transcription from a Drosophila hsp70 gene in vitro.