ライフサイエンスコーパス: drug sensitivity

1 etastable bioanalyte toward predicting tumor drug sensitivity.

2 pply MiSL to pinpoint genetic biomarkers for drug sensitivity.

3 s displayed decreased stemness and increased drug sensitivity.

4 tem to study the interplay of metabolism and drug sensitivity.

5 of rational combination therapies to restore drug sensitivity.

6 ergy status of the cell, PXR regulation, and drug sensitivity.

7 nts, mutations can have important effects on drug sensitivity.

8 t component of tumor fitness and can predict drug sensitivity.

9 cing unique growth physiologies and reducing drug sensitivity.

10 , decreased HOX gene expression and restored drug sensitivity.

11 OK2, miR-193a, and others) restored platinum drug sensitivity.

12 erturbed genes cooperatively associated with drug sensitivity.

13 ns on tumorigenesis, cancer progression, and drug sensitivity.

14 related modules as top differential ones for drug sensitivity.

15 el to study the effects of the cell cycle on drug sensitivity.

16 ought to represent a biomarker predictive of drug sensitivity.

17 nd high MYC expression predicts anti-mitotic drug sensitivity.

18 nisms, establishing an individual profile of drug sensitivity.

19 nt channels can exhibit dramatically reduced drug sensitivity.

20 ce that RNA editing could selectively affect drug sensitivity.

21 otentially linking upregulation to increased drug sensitivity.

22 ortant determinants of cation permeation and drug sensitivity.

23 n (Y652W) into S620T hERG1 partially rescued drug sensitivity.

24 ia (CLL) cells, thereby also affecting their drug sensitivity.

25 breast cancer cell line was found to restore drug sensitivity.

26 ith a unique epigenetic signature to predict drug sensitivity.

27 n profoundly influence parasite genetics and drug sensitivity.

28 f these lncRNAs exhibited a clear phenotype: drug sensitivity.

29 effects of NOX-A12 on CLL cell migration and drug sensitivity.

30 e diagnostic tools for tuberculosis (TB) and drug sensitivity.

31 e HGF receptor MET abrogates HGF's rescue of drug sensitivity.

32 several parasite lines to test the effect on drug sensitivity.

33 sion of NICD1 reversed the action of DAPT on drug sensitivity.

34 und impact in their metabolism, biology, and drug sensitivity.

35 nts upon erlotinib treatment correlates with drug sensitivity.

36 , elevated VTA BDNF may be a risk factor for drug sensitivity.

37 lls lacking H3K4 methylation have antifungal drug sensitivity.

38 expression can affect platelet function and drug sensitivity.

39 EN in PTEN-null breast cancer cells restored drug sensitivity.

40 inkages between genetic profile and targeted-drug sensitivity.

41 age, and gene-expression-based predictors of drug sensitivity.

42 mor growth in xenograft models and increased drug sensitivity.

43 e confounding effects of tumor CIN status on drug sensitivity.

44 of APP played a pivotal role in determining drug sensitivity.

45 whereas most other mutations did not affect drug sensitivity.

46 ntextualize proteins and p-sites and predict drug sensitivity.

47 tate, and we validate metabolites that alter drug sensitivity.

48 reened a panel of 53 melanoma cell lines for drug sensitivity.

49 ide valuable insight on tumour evolution and drug sensitivity.

50 to better understand cancer dependencies and drug sensitivity.

51 ck circuit remains mutation-free and regains drug sensitivity.

52 necting shared perturbations to differential drug sensitivity.

53 relevance regarding replication fitness and drug sensitivity.

54 NA translation that evolves in parallel with drug sensitivity.

55 ation technique, and apply it to investigate drug sensitivity.

56 orrelating genomic mutagenic phenotypes with drug sensitivity.

57 EMT as a source of phenotypic variability in drug sensitivity.

58 cell-specific dynamic signaling pathways and drug sensitivity.

59 i-cancer treatment can uncover biomarkers of drug sensitivity.

60 mours, useful for revealing patient-specific drug sensitivities.

61 clonal composition, genetic alterations, and drug sensitivities.

62 etween parasite isolates that exhibit varied drug sensitivities.

63 s, including life span, budding pattern, and drug sensitivities.

64 how does hypoxia play a role in anti-cancer drug sensitivity?

65 sis, an in silico screening of a database of drug sensitivities across 39 cancer cell lines (JFCR39),

66 e of matrix stiffness in growth kinetics and drug sensitivity against standard chemotherapy in vivo.

67 odel that predicts clinical response through drug sensitivity analyses and determined that cellular a

68 GECO's mutational enrichment and pairwise drug sensitivity analyses functions that follow the deco

69 Data for laboratory isolates, including drug sensitivities and 24-mycobacterial interspersed rep

70 three strains of gametocytes with different drug sensitivities and geographical origins, 3D7, HB3 an

71 minative latent characteristics that predict drug sensitivity and are associated with specific molecu

72 ral biomarkers for clinical determination of drug sensitivity and drug efficacy in nucleotide triphos

73 ient-derived melanoids for prognostic use of drug sensitivity and further underscoring the beneficial

74 Drug sensitivity and gene dependency screens demonstrate

75 is of great interest to jointly analyze the drug sensitivity and gene expression data from the same

76 ovides a unique resource incorporating large drug sensitivity and genomic datasets to facilitate the

77 a that inhibition of autophagy will increase drug sensitivity and kill more cancer cells.

78 These cells demonstrate >100-fold reduced drug sensitivity and maintain viability via engagement o

79 ering ~500-fold in drug response, determined drug sensitivity and marker segregation in clonally deri

80 Interspecies differences in drug sensitivity and mechanistic profiles, low predictiv

81 The method is exemplified by application to drug sensitivity and microRNA expression data from a pan

82 behavioral responses to drugs of abuse with drug sensitivity and motivation peaking during the dark

83 se complex processes, identify biomarkers of drug sensitivity and predict the response to a drug.

84 Drug sensitivity and resistance are conventionally quant

85 Here we combine comprehensive drug sensitivity and resistance profiling of patient cel

86 Drug sensitivity and resistance testing on diagnostic le

87 Our results explain the basis for drug sensitivity and resistance to an exceptionally pote

88 es three subtypes of lung SCC that differ in drug sensitivity and shows a novel mechanism of miR-29b

89 Adequate infrastructure for testing drug sensitivity and sufficient evidence of first-line r

90 n of miR-23b cluster or miR-125a-5p enhanced drug sensitivity and suppressed invasiveness of NSCLC ce

91 reprograms melanoma metabolism to influence drug sensitivity and survival.

92 t CDR of patients and identify biomarkers of drug sensitivity and survival.

93 Epigenomic subpopulations in cancer impact drug sensitivity and the clonal dynamics of cancer evolu

94 s interact, we investigated their effects on drug sensitivity and viral fitness.

95 ed ABCC4 from the plasma membrane, increased drug sensitivity, and abrogated MPP1-dependent hematopoi

96 OM permeability, lipopolysaccharide levels, drug sensitivity, and cell death in stationary phase.

97 sistance, increases the predictive power for drug sensitivity, and helps identify effective drug comb

98 detect a population which shows differential drug sensitivity, and imply that treatment of patients c

99 pression of PTEN in PTEN-null cells restored drug sensitivity, and knockdown of PTEN promoted drug re

100 ient, in terms of their malignant potential, drug sensitivity, and their potential to metastasize and

101 ltiple biomarkers that contribute jointly to drug sensitivity, and to identify combination therapies

102 e find that differences in general levels of drug sensitivity are driven by biologically relevant pro

103 data tend to exhibit improved prediction of drug sensitivity as compared with genomic and transcript

104 known drug-target relationships and overall drug sensitivity as compared with genomic or transcripto

105 tated or deleted in human tumors, may impact drug sensitivity, as exemplified by triple-negative brea

106 Drug sensitivity assays revealed resistance to oseltamiv

107 al impedance platform over standard in vitro drug sensitivity assays were demonstrated quantitatively

108 ractory to sodium stibogluconate in in-vitro drug sensitivity assays.

109 ganoids can be xenografted, enabling in vivo drug-sensitivity assays.

110 atient-derived models could predict targeted drug sensitivity associated with actionable mutations in

111 Quantitatively predicting changes in drug sensitivity associated with residue mutations is a

112 ging the latest knowledge on mutation-cancer drug sensitivity associations and the results from large

113 apy may have future application in restoring drug sensitivity at relapse.

114 We discover lineage-specific drug sensitivities based on subcategorization of gynecol

115 matically analyze mutations affecting cancer drug sensitivity based on individual genomic profiles.

116 cused on identifying molecular biomarkers of drug sensitivity based on queries of specific anticancer

117 e that neoplastic cells exhibit differential drug sensitivity based on their residence in specific ce

118 d R5 cells, establishing that differences in drug sensitivities between sublines were independent of

119 ontrivial, complex ways to the difference in drug sensitivity between Emu-myc Arf-/- and Emu-myc p53-

120 apoptotic regulators that are predictive of drug sensitivity (BIM, caspase-3, BCL-XL) and resistance

121 vity across NBL cell lines, thus providing a drug sensitivity biomarker.

122 However, drug sensitivity biomarkers in esophageal squamous cell

123 Drug sensitivity biomarkers were identified by performin

124 cial pan-cancer cell line models to identify drug sensitivity biomarkers.

125 a3 to suppress tumor progression and enhance drug sensitivity by exploiting TAMs to trigger ADCC.

126 idly detects bacterial growth and determines drug sensitivity by measuring changes in the suspension'

127 we found that most cells can be rescued from drug sensitivity by simply exposing them to one or more

128 Thus, parasites selected for decreased drug sensitivity can appear long after predicted exposur

129 Herein we ask whether or not drug sensitivity can be designed into Klp61F.

130 ted in both drug resistance and personalized drug sensitivity can be predicted in a high-throughput f

131 Figure 2 demonstrates resistance to drug sensitivity conferred by co-culture with some strom

132 mechanism nor the uniformity of anti-mitotic drug sensitivity connected with mutant KRAS expression a

133 we considered whether factors that enhanced drug sensitivity could be repurposed as therapeutics and

134 f-of-principle case, we showed that in vitro drug sensitivity could predict both a clinical response

135 olecular markers of drug response, cell line drug sensitivity data are integrated with large genomic

136 GDSC currently contains drug sensitivity data for almost 75 000 experiments, des

137 Such drug sensitivity data for cancer cell lines provide sugg

138 aluated using microarray gene expression and drug sensitivity data from human and canine cancer cell

139 Comparisons of gene essentiality with drug sensitivity data suggest potential resistance mecha

140 clinical platform generating a compendium of drug sensitivity data totalling >4,000 assays testing 16

141 sues (n=60), and integrated with genomic and drug sensitivity data.

142 intly analyze the paired gene expression and drug sensitivity datasets measured across the same panel

143 he utility of our package in comparing large drug sensitivity datasets, such as the Genomics of Drug

144 fying genetic biomarkers of synthetic lethal drug sensitivity effects provides one approach to the de

145 This study unveils a novel collateral drug sensitivity elicited by combining copper chelators

146 signaling dynamics correlated strongly with drug sensitivity for 14 of the drugs, 9 of which had no

147 uilt gene expression-based models to predict drug sensitivity for 265 common anticancer compounds.

148 he simulations predicted the ranked order of drug sensitivity for indomethacin, aspirin, MRS-2179 (a

149 ies also reveal unique signature patterns of drug sensitivity for inhibition of tyrosine autophosphor

150 ossibility of identifying genomic markers of drug sensitivity for novel compounds on novel cell lines

151 s a simple semiempirical method to determine drug sensitivity for positive secondary ions.

152 ion may come from diverse sources, including drug sensitivities, gene ontology biological processes,

153 OS, providing a mechanistic link between the drug sensitivity, gene expression, and pathogenesis phen

154 ature of cancer, but its global influence on drug sensitivity has not been examined.

155 Predictive models of in vitro drug sensitivity have previously been constructed using

156 Analysis of gene set enrichment and drug sensitivity identified an immune-evasion subtype th

157 revented core complex formation and restored drug sensitivity, impairing the signaling pathways invol

158 otential solution to this may lie in finding drug sensitivities in the resistant population, termed c

159 We measured gene expression and drug sensitivity in 15 pediatric T-ALL cell lines to fin

160 The Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line E

161 harmacogenomic databases such as Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Cell Line E

162 3) in cancer cell lines from the Genomics of Drug Sensitivity in Cancer (GDSC) database.

163 Line Encyclopedia (CCLE) and the Genomics of Drug Sensitivity in Cancer (GDSC), we determined the opt

164 ensitivity datasets, such as the Genomics of Drug Sensitivity in Cancer and the Cancer Cell Line Ency

165 is for investigating genomic associations of drug sensitivity in cancer cell lines, but it can be app

166 tematic identification of genomic markers of drug sensitivity in cancer cells" by Garnett and colleag

167 ores the important role of hCtr1 in platinum-drug sensitivity in cancer chemotherapy.

168 models and models generated from Genomics of Drug Sensitivity in Cancer database shows the ability of

169 drug response profiles from the Genomics of Drug Sensitivity in Cancer database, we identified mutat

170 armacogenomics profiles from the Genomics of Drug Sensitivity in Cancer database, we show that the ne

171 roject Achilles and one from the Genomics of Drug Sensitivity in Cancer project, UNCOVER identifies s

172 .Z.2 as a mediator of cell proliferation and drug sensitivity in malignant melanoma, holding translat

173 Inhibition of IL-6 restored drug sensitivity in patient-derived organoid cultures an

174 e show that variability in general levels of drug sensitivity in pre-clinical cancer models confounds

175 utated-B-RAF inhibitors and possibly restore drug sensitivity in resistant tumors.

176 ts in physiological abnormalities or affects drug sensitivity in selected populations (e.g., those wi

177 tory strains that show little differences in drug sensitivity in standard in vitro assays exhibit sub

178 etency of macrophage fusion as well as their drug sensitivity in the biomaterial implanted tissue env

179 t of proteins that effectively reconstituted drug sensitivity in the cell-free screen and included a

180 Ornithine uptake and the modulation of drug sensitivity in Trypanosoma brucei.

181 ion by E1B-55K for cell cycle regulation and drug sensitivity in tumor cells has not been examined.

182 nisms, including consequences for inhibitory drug sensitivity, insights that may inform the developme

183 This fibroblast-mediated reduction in drug sensitivity involves increased expression of antiap

184 Interestingly, we find that drug sensitivity is highest in tumor cells with a mesenc

185 The role of TME in modulating tumor drug sensitivity is increasingly recognized and targetin

186 This model, developed using FM-HCR and drug sensitivity measurements in 24 human lymphoblastoid

187 e resource for cancer researchers, providing drug sensitivity, molecular and phenotypic data for a ra

188 an in cancer cells, may be attributed to low drug sensitivity, nevertheless the study invited close a

189 MAR revealed heterogeneity in drug sensitivity not only between different tumors, but

190 es lacking SMARCB1 are vital determinants of drug sensitivity, not just to TOP2A-targeted agents, but

191 toward WT tumors, confirming the collateral drug sensitivities observed in vitro.

192 genes were verified to be predictive of the drug sensitivities of different glioma cell lines, in co

193 We determined drug sensitivities of the subtypes in primary tumors usi

194 Using the drug sensitivity of cancer cell lines as a benchmark, we

195 insights into the mechanisms underlying the drug sensitivity of cancer cell lines.

196 actions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 dru

197 We then examine the drug sensitivity of cell-to-cell spread of HIV, a mode o

198 terogeneous leukemia-initiating capacity and drug sensitivity of CML LTHSCs and suggest that high MPL

199 manipulation of SALL4 expression can affect drug sensitivity of endometrial cancer cells to carbopla

200 We characterized the landscape and drug sensitivity of ERBB2 (HER2) mutations in cancers.

201 The drug sensitivity of human BGC823 gastric cancer cells to

202 Gant61 monotherapy did not alter the drug sensitivity of naive cells, but could reverse the r

203 thus resulting in successful restoration of drug sensitivity of OVCAR8/ADR cells to Pgp-transportabl

204 FA signaling pathways which lead to improved drug sensitivity of PCa.

205 ence that synonymous mutations can alter the drug sensitivity of proteins.

206 otentiating oncogenic signaling and reducing drug sensitivity of RAS-mutant cells.

207 Thus, the biology and drug sensitivity of RC clinical isolates can be efficien

208 ize a functional assay to assess the ex vivo drug sensitivity of single multiple myeloma cells based

209 region fine-tunes calcium responsiveness and drug sensitivity of the anchored phosphatase.

210 In several cases, such heterogeneity in drug sensitivity of tumors is driven by stochastic and r

211 The innate drug-sensitivity of the DNA binding and cleavage region

212 For most drugs, sensitivity of skin testing is higher in immediat

213 an EGFR mutation known to be associated with drug sensitivity or objective clinical benefit from trea

214 crochannel resonator, accurately defined the drug sensitivity or resistance of glioblastoma and B-cel

215 in individual virions distinguishes between drug sensitivity or resistance to protease inhibitors in

216 implicated in treatment-related toxicity and drug sensitivity or resistance, depending on whether the

217 hibit L. donovani infection, irrespective of drug sensitivity or resistance.

218 externalizing traits, consumption drive, and drug sensitivity or tolerance) that combine with key env

219 Linking molecular profiles with drug sensitivity patterns identifies novel biomarkers, i

220 genes that most likely explain the observed drug sensitivity patterns.

221 However, despite the null-like drug sensitivity phenotype, chemical cross-linking analy

222 s (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms.

223 This study establishes benchmarks for drug sensitivity prediction and identifies approaches th

224 of random forest based methods in NCI-DREAM drug sensitivity prediction challenge.

225 Drug sensitivity prediction for individual tumors is a s

226 ompared to state-of-the-art methodologies in drug sensitivity prediction scenarios using synthetic da

227 odels and algorithms to solve the problem of drug sensitivity prediction, biomarker identification an

228 To assess the preclinical feasibility of drug sensitivity prediction, several studies have measur

229 ine Encyclopedia to increase the accuracy of drug sensitivity prediction.

230 hnologies and DL-based approaches related to drug sensitivity predictions.

231 For designing a drug sensitivity predictive model from such a database,

232 rug to treat this cancer type that mimic the drug sensitivity profile in PDX model, further confirmin

233 Here, we evaluate the in vitro drug sensitivity profile of normally-developing P. falci

234 e-response curve fails to provide the entire drug sensitivity profile which can be used to design the

235 cells-of-origin may critically determine the drug sensitivity profiles of mammary neoplasia.

236 nic parasite line showed similar fitness and drug sensitivity profiles of selected compounds to wild

237 elationships connecting genome, proteome and drug sensitivity profiles present a major bottleneck in

238 Analysis of the resulting drug sensitivity profiles provides novel information on

239 Although phenotypic drug sensitivity profiles show significant diversity, th

240 tion, high-throughput drug perturbation, and drug sensitivity profiles, enabling drug classification

241 By comparing drug sensitivity profiles, we predicted BUB1B(S) cells t

242 mplex relationships connecting genotypes and drug sensitivity profiles.

243 showed that our prediction agrees with their drug-sensitivity profiles.

244 Drug-sensitivity profiling of RET(L881V) revealed that i

245 perturbation gene expression signatures and drug sensitivity provide a powerful framework to develop

246 g mutations and gene- expression patterns on drug sensitivity, providing hope that future treatment o

247 For problem use of illicit and prescription drugs, sensitivity ranged from 0.82 (CI, 0.76 to 0.87) f

248 e stage- and strain-dependent differences in drug sensitivity reflect differential response lag times

249 aches integrated cistrome, transcriptome and drug sensitivity relationships to reveal that NCOR1 func

250 Existing approaches to predicting drug sensitivity rely primarily on profiling of cancer c

251 regarding somatic mutation for prediction of drug sensitivity remains controversial.

252 osphorylation-related signaling networks and drug sensitivity/resistance in the era of precision onco

253 mors, find that many of these associate with drug sensitivity/resistance, and highlight the importanc

254 proposed droplet-based AST, including rapid drug sensitivity response, morphological analysis, and h

255 Notably, drug sensitivity results directly from tgp1(+) expressio

256 ently of tuberculin skin test and index-case drug sensitivity results.

257 we couple pathway knowledge with large-scale drug sensitivity, RNAi, and CRISPR-Cas9 screening data f

258 Finally, GECO's drug sensitivity screen function can be used to identify

259 Using comprehensive drug-sensitivity screening in PP2A-modulated cells to ev

260 Parallel siRNA and drug sensitivity screens showed that the clinical CDK4/6

261 ta with functional characterizations such as drug-sensitivity, short hairpin RNA knockdown and CRISPR

262 Thus, genome-informed drug sensitivity studies identify a subset of GBMs likel

263 Results from drug sensitivity studies with beta-lactamase enzymes are

264 suppressing genes on the basis of the shared drug sensitivity suppression and similar genetic interac

265 monstrated that the function of HSP-16.48 in drug sensitivity surprisingly was independent of chapero

266 tment regimens are designed based on culture-drug sensitivity test patterns, previous drug-exposures

267 tecting rifampin resistance using phenotypic drug sensitivity testing (DST) as the reference standard

268 ically relevant time scale some weeks before drug sensitivity testing (DST) data are available, and t

269 gnosis in health-care settings in Kenya, and drug sensitivity testing in Moldova.

270 Drug sensitivity testing of CTC lines with multiple muta

271 Subsequent drug sensitivity testing revealed over 100-fold increase

272 Parasite clearance half-life and in vitro drug sensitivity testing were performed using standard m

273 The combination of sophisticated drug sensitivity testing with advanced in vitro tumor mo

274 plications, including regenerative medicine, drug sensitivity testing, gene expression profiling and

275 a cornerstone of tuberculosis diagnosis and drug sensitivity testing.

276 ntry of high tuberculosis burden should have drug-sensitivity testing on isolates to ensure appropria

277 isen from diploid cell lines displayed lower drug sensitivity than their diploid parental cells only

278 to identify previously occult biomarkers of drug sensitivity that can aid in the identification of p

279 oproteins provide information for predicting drug sensitivity that is not available from the correspo

280 ance the generation of important insights to drug sensitivity that will lead to improved precision me

281 Ex vivo drug sensitivity to 122 small-molecule inhibitors reveal

282 These proteins could predict drug sensitivity to BRAF-MEK concurrent inhibition in ce

283 e with lentiviral TR4 siRNA led to increased drug sensitivity to the two commonly used chemotherapeut

284 of slow-cycling cells that can either regain drug sensitivity upon treatment discontinuation or acqui

285 s a significant improvement in prediction of drug sensitivity using genes identified by ProGENI compa

286 Drug sensitivity varied dramatically across individuals

287 Drug sensitivity was restored with co-treatment of eithe

288 Drug sensitivity was reversed by dimedone treatment, ind

289 es using in vitro transformation assays, and drug sensitivities were validated with the use of assays

290 Similar levels of drug sensitivity were displayed by the three most common

291 us or MYC expression levels and anti-mitotic drug sensitivity when surveying a large database of anti

292 rating their dynamics, regulation and unique drug sensitivities, which were predictive of clinical re

293 ned inhibition, is sufficient to enhance AML drug sensitivity, which provides a novel therapeutic str

294 increased AKT phosphorylation and decreased drug sensitivity, which was attenuated by GLI1 inhibitio

295 Knockdown of CDK6 restored drug sensitivity, while enforced overexpression of CDK6

296 rtefactual correlations between genotype and drug sensitivity, while obscuring valuable biological in

297 The measurements of loci specific epi-drugs sensitivities will pave the way to the development

298 patient samples revealed a wide diversity of drug sensitivities, with 70% of the clinical specimens e

299 branch point (BP) region strongly influence drug sensitivity, with additional functional BPs reducin

300 Since the four subtypes exhibit differential drug sensitivity, with NEv2 consistently least sensitive