Abstract 4149: Extensive characterization of the adenosine pathway in human solid tumors gives a hint on cancer indication selection for the A2Areceptor antagonist EOS100850

Author(s):  
Noemie Wald ◽  
Chiara Martinoli ◽  
Marjorie Mercier ◽  
Annelise Hermant ◽  
Florence Nyawouame ◽  
...  
1981 ◽  
Vol 6 (3) ◽  
Author(s):  
HarryK. Slocum ◽  
ZlatkoP. Pavelic ◽  
PeterM. Kanter ◽  
NormaJ. Nowak ◽  
YoucefM. Rustum

1994 ◽  
Vol 21 (5) ◽  
pp. 771-774
Author(s):  
Silvana Del Vecchio ◽  
M.Patrizia Stoppelli ◽  
Maria V. Carriero ◽  
Rosa Fonti ◽  
Ornella Massa ◽  
...  

Author(s):  
Yohei Koizumi ◽  
Masayuki Kuzuhara ◽  
Masashi Omiya ◽  
Teruyuki Hirano ◽  
John Wisniewski ◽  
...  

Abstract We present the optical spectra of 338 nearby M dwarfs, and compute their spectral types, effective temperatures (Teff), and radii. Our spectra were obtained using several optical spectrometers with spectral resolutions that range from 1200 to 10000. As many as 97% of the observed M-type dwarfs have a spectral type of M3–M6, with a typical error of 0.4 subtype, among which the spectral types M4–M5 are the most common. We infer the Teff of our sample by fitting our spectra with theoretical spectra from the PHOENIX model. Our inferred Teff is calibrated with the optical spectra of M dwarfs whose Teff have been well determined with the calibrations that are supported by previous interferometric observations. Our fitting procedures utilize the VO absorption band (7320–7570 Å) and the optical region (5000–8000 Å), yielding typical errors of 128 K (VO band) and 85 K (optical region). We also determine the radii of our sample from their spectral energy distributions. We find most of our sample stars have radii of <0.6 R⊙, with the average error being 3%. Our catalog enables efficient sample selection for exoplanet surveys around nearby M-type dwarfs.


2014 ◽  
Vol 6 (8) ◽  
Author(s):  
Winston Timp ◽  
Hector Corrada Bravo ◽  
Oliver G McDonald ◽  
Michael Goggins ◽  
Chris Umbricht ◽  
...  

1992 ◽  
Vol 12 (5) ◽  
pp. 2372-2382
Author(s):  
K M Arndt ◽  
S L Ricupero ◽  
D M Eisenmann ◽  
F Winston

A mutation in the gene that encodes Saccharomyces cerevisiae TFIID (SPT15), which was isolated in a selection for mutations that alter transcription in vivo, changes a single amino acid in a highly conserved region of the second direct repeat in TFIID. Among eight independent spt15 mutations, seven cause this same amino acid change, Leu-205 to Phe. The mutant TFIID protein (L205F) binds with greater affinity than that of wild-type TFIID to at least two nonconsensus TATA sites in vitro, showing that the mutant protein has altered DNA binding specificity. Site-directed mutations that change Leu-205 to five different amino acids cause five different phenotypes, demonstrating the importance of this amino acid in vivo. Virtually identical phenotypes were observed when the same amino acid changes were made at the analogous position, Leu-114, in the first repeat of TFIID. Analysis of these mutations and additional mutations in the most conserved regions of the repeats, in conjunction with our DNA binding results, suggests that these regions of the repeats play equivalent roles in TFIID function, possibly in TATA box recognition.


2013 ◽  
Vol 31 (15) ◽  
pp. 1874-1884 ◽  
Author(s):  
Rodrigo Dienstmann ◽  
Jordi Rodon ◽  
Jordi Barretina ◽  
Josep Tabernero

Recent discoveries of genomic alterations that underlie and promote the malignant phenotype, together with an expanded repertoire of targeted agents, have provided many opportunities to conduct hypothesis-driven clinical trials. The ability to profile each unique cancer for actionable aberrations by using high-throughput technologies in a cost-effective way provides unprecedented opportunities for using matched therapies in a selected patient population. The major challenges are to integrate and make biologic sense of the substantial genomic data derived from multiple platforms. We define two different approaches for the analysis, interpretation, and clinical applicability of genomic data: (1) the genomically stratified model originates from the “one test-one drug” paradigm and is currently being expanded with an upfront multicategorical approach following recent advances in multiplexed genotyping platforms; and (2) the comprehensive assessment model is based on whole-genome, -exome, and -transcriptome data and allows identification of novel drivers and subsequent therapies in the experimental setting. Tumor heterogeneity and evolution of the diverse populations of cancer cells during cancer progression, influenced by the effects of systemic treatments, will need to be addressed in the new scenario of early drug development. Logistical issues related to prescreening strategies and trial allocation, in addition to concerns in the economic and ethical domains, must be taken into consideration. Here we present a historical view of how increased understanding of cancer genomics has been translated to the clinic and discuss the prospects and challenges for further implementation of a personalized treatment strategy for human solid tumors.


Sign in / Sign up

Export Citation Format

Share Document