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Search: WFRF:(Baskaran Sathishkumar) > Comparative drug pa...

Comparative drug pair screening across multiple glioblastoma cell lines reveals novel drug-drug interactions

Schmidt, L. (author)
Kling, T. (author)
Monsefi, N. (author)
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Olsson, M. (author)
Hansson, C. (author)
Baskaran, Sathishkumar (author)
Uppsala universitet,Cancer och vaskulärbiologi
Lundgren, Bo (author)
Stockholms universitet,Institutionen för biokemi och biofysik,Science for Life Laboratory (SciLifeLab)
Martens, Ulf (author)
Stockholms universitet,Institutionen för biokemi och biofysik,Science for Life Laboratory (SciLifeLab)
Häggblad, Maria (author)
Stockholms universitet,Institutionen för biokemi och biofysik,Science for Life Laboratory (SciLifeLab)
Westermark, Bengt (author)
Uppsala universitet,Cancer och vaskulärbiologi
Nilsson, Karin Forsberg (author)
Uppsala universitet,Cancer och vaskulärbiologi
Uhrbom, Lene (author)
Uppsala universitet,Cancer och vaskulärbiologi
Karlsson-Lindahl, L. (author)
Gerlee, Philip, 1980 (author)
Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper, matematik,Department of Mathematical Sciences, Mathematics,Chalmers tekniska högskola,Chalmers University of Technology,University of Gothenburg
Nelander, Sven (author)
Uppsala universitet,Cancer och vaskulärbiologi
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 (creator_code:org_t)
2013-10-06
2013
English.
In: Neuro-Oncology. - : Oxford University Press (OUP). - 1522-8517 .- 1523-5866. ; 15:11, s. 1469-1478
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Glioblastoma multiforme (GBM) is the most aggressive brain tumor in adults, and despite state-of-the-art treatment, survival remains poor and novel therapeutics are sorely needed. The aim of the present study was to identify new synergistic drug pairs for GBM. In addition, we aimed to explore differences in drug-drug interactions across multiple GBM-derived cell cultures and predict such differences by use of transcriptional biomarkers. We performed a screen in which we quantified drug-drug interactions for 465 drug pairs in each of the 5 GBM cell lines U87MG, U343MG, U373MG, A172, and T98G. Selected interactions were further tested using isobole-based analysis and validated in 5 glioma-initiating cell cultures. Furthermore, drug interactions were predicted using microarray-based transcriptional profiling in combination with statistical modeling. Of the 5 465 drug pairs, we could define a subset of drug pairs with strong interaction in both standard cell lines and glioma-initiating cell cultures. In particular, a subset of pairs involving the pharmaceutical compounds rimcazole, sertraline, pterostilbene, and gefitinib showed a strong interaction in a majority of the cell cultures tested. Statistical modeling of microarray and interaction data using sparse canonical correlation analysis revealed several predictive biomarkers, which we propose could be of importance in regulating drug pair responses. We identify novel candidate drug pairs for GBM and suggest possibilities to prospectively use transcriptional biomarkers to predict drug interactions in individual cases.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Neurologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Neurology (hsv//eng)
NATURVETENSKAP  -- Biologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences (hsv//eng)

Keyword

drug combination responses
glioblastoma therapy
glioblastoma stem cell
cultures
predictive medicine
antidepressant sertraline
tumor
gene
classification
therapeutics
temozolomide
combination
progression
carcinoma
apoptosis
tumor

Publication and Content Type

ref (subject category)
art (subject category)

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