Eintrag weiter verarbeiten
Abstract B65: MicroRNAs in cancer drug resistance and sensitivity
Gespeichert in:
| Zeitschriftentitel: | Clinical Cancer Research |
|---|---|
| Personen und Körperschaften: | |
| In: | Clinical Cancer Research, 18, 2012, 10_Supplement, S. B65-B65 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
American Association for Cancer Research (AACR)
|
| Schlagwörter: |
| author_facet |
Zhu, Jian Zhu, Jian |
|---|---|
| author |
Zhu, Jian |
| spellingShingle |
Zhu, Jian Clinical Cancer Research Abstract B65: MicroRNAs in cancer drug resistance and sensitivity Cancer Research Oncology |
| author_sort |
zhu, jian |
| spelling |
Zhu, Jian 1078-0432 1557-3265 American Association for Cancer Research (AACR) Cancer Research Oncology http://dx.doi.org/10.1158/1078-0432.mechres-b65 <jats:title>Abstract</jats:title> <jats:p>microRNAs are small noncoding RNAs of 18–25 nucleotides that have been shown to regulate gene expression posttranscriptionally and play fundamental roles in diverse biological and pathological processes. MiRNApedia is an in silico discovery tool designed to integrate all microRNA-related information including genetic variation, gene expression, epigenetic regulation, pathways, diseases, clinical outcomes and particularly drug actions. The system documented more than 1,000 microRNAs and 600 therapeutic and experimental compounds including well-known cancer drugs cisplatin, doxorubicin, 5-flouracil, gemicitabine, paclitaxel, docetaxal, imatinib, vorinostat, sorafenib and gefitinib etc. For each compound, microRNAs and genes related to its sensitivity and function were compiled from literature and used to construct comprehensive drug-gene-microRNA networks. MicroRNAs played important roles in determining resistance and sensitivity of cancer drugs. For example, miR-21 reduced sensitivities to daunorubicin, topotecan, 5-FU, taxol, doxorubicin, docetaxel, ara-C, arsenic trioxide, gemcitabine and dexamethasome, while miR-146a increased sensitivity to bleomycin and over-expression of miR-221 conferred resistance to tamoxifen. Multiple microRNAs might be involved in the efficacy of a single drug. MiRs -98, -214, -106a, -125b and -630 contributed to cisplatin resistance, while -451, -181a, -148a, -138 and let-7i enhanced its sensitivity. Meanwhile, cisplatin was shown to down-regulate miRs -150 and -106 while up-regulated miRs -34, -16, -17-5p and -125. Drug combination would be the choice to overcome resistance in mono-therapies. Prior to experimental testing, the combination effects of multiple drugs could be assessed computationally by combining annotated information in microRNA targets, signaling pathways and transcriptional regulations etc. For example, trichostatin A (TSA), a HDAC inhibitor, might enhance sensitivity of cisplatin by up-regulating p53 and its transcriptional target miR-34 which subsequently down-regulated BCL2, a well-known drug resistance factor. However, if miR-125b, another transcriptional target of p53, was up-regulated, the combination might turn out to be antagonistic. Mechanistically, miR-125b targeted BAK1 which was required for cisplatin sensitivity. Such in silico modeling exercises not only predicted synergism or antagonism, but also identified underlined drivers which could serve as biomarkers for desired therapeutic effects. The potential biomarkers identified by the network modeling approach could be used to guide selection of experimental system (e.g., cell line models) and monitor the combination effectiveness. The present study devised a mechanism to systematically capture microRNA information in regards to cancer drug resistance and established a computational framework to identify potential drug combinations to overcome resistance in cancer therapies.</jats:p> Abstract B65: MicroRNAs in cancer drug resistance and sensitivity Clinical Cancer Research |
| doi_str_mv |
10.1158/1078-0432.mechres-b65 |
| facet_avail |
Online Free |
| finc_class_facet |
Medizin |
| format |
ElectronicArticle |
| fullrecord |
blob:ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTE1OC8xMDc4LTA0MzIubWVjaHJlcy1iNjU |
| id |
ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTE1OC8xMDc4LTA0MzIubWVjaHJlcy1iNjU |
| institution |
DE-15 DE-Pl11 DE-Rs1 DE-14 DE-105 DE-Ch1 DE-L229 DE-D275 DE-Bn3 DE-Brt1 DE-Zwi2 DE-D161 DE-Zi4 DE-Gla1 |
| imprint |
American Association for Cancer Research (AACR), 2012 |
| imprint_str_mv |
American Association for Cancer Research (AACR), 2012 |
| issn |
1078-0432 1557-3265 |
| issn_str_mv |
1078-0432 1557-3265 |
| language |
English |
| mega_collection |
American Association for Cancer Research (AACR) (CrossRef) |
| match_str |
zhu2012abstractb65micrornasincancerdrugresistanceandsensitivity |
| publishDateSort |
2012 |
| publisher |
American Association for Cancer Research (AACR) |
| recordtype |
ai |
| record_format |
ai |
| series |
Clinical Cancer Research |
| source_id |
49 |
| title |
Abstract B65: MicroRNAs in cancer drug resistance and sensitivity |
| title_unstemmed |
Abstract B65: MicroRNAs in cancer drug resistance and sensitivity |
| title_full |
Abstract B65: MicroRNAs in cancer drug resistance and sensitivity |
| title_fullStr |
Abstract B65: MicroRNAs in cancer drug resistance and sensitivity |
| title_full_unstemmed |
Abstract B65: MicroRNAs in cancer drug resistance and sensitivity |
| title_short |
Abstract B65: MicroRNAs in cancer drug resistance and sensitivity |
| title_sort |
abstract b65: micrornas in cancer drug resistance and sensitivity |
| topic |
Cancer Research Oncology |
| url |
http://dx.doi.org/10.1158/1078-0432.mechres-b65 |
| publishDate |
2012 |
| physical |
B65-B65 |
| description |
<jats:title>Abstract</jats:title>
<jats:p>microRNAs are small noncoding RNAs of 18–25 nucleotides that have been shown to regulate gene expression posttranscriptionally and play fundamental roles in diverse biological and pathological processes. MiRNApedia is an in silico discovery tool designed to integrate all microRNA-related information including genetic variation, gene expression, epigenetic regulation, pathways, diseases, clinical outcomes and particularly drug actions. The system documented more than 1,000 microRNAs and 600 therapeutic and experimental compounds including well-known cancer drugs cisplatin, doxorubicin, 5-flouracil, gemicitabine, paclitaxel, docetaxal, imatinib, vorinostat, sorafenib and gefitinib etc. For each compound, microRNAs and genes related to its sensitivity and function were compiled from literature and used to construct comprehensive drug-gene-microRNA networks. MicroRNAs played important roles in determining resistance and sensitivity of cancer drugs. For example, miR-21 reduced sensitivities to daunorubicin, topotecan, 5-FU, taxol, doxorubicin, docetaxel, ara-C, arsenic trioxide, gemcitabine and dexamethasome, while miR-146a increased sensitivity to bleomycin and over-expression of miR-221 conferred resistance to tamoxifen. Multiple microRNAs might be involved in the efficacy of a single drug. MiRs -98, -214, -106a, -125b and -630 contributed to cisplatin resistance, while -451, -181a, -148a, -138 and let-7i enhanced its sensitivity. Meanwhile, cisplatin was shown to down-regulate miRs -150 and -106 while up-regulated miRs -34, -16, -17-5p and -125. Drug combination would be the choice to overcome resistance in mono-therapies. Prior to experimental testing, the combination effects of multiple drugs could be assessed computationally by combining annotated information in microRNA targets, signaling pathways and transcriptional regulations etc. For example, trichostatin A (TSA), a HDAC inhibitor, might enhance sensitivity of cisplatin by up-regulating p53 and its transcriptional target miR-34 which subsequently down-regulated BCL2, a well-known drug resistance factor. However, if miR-125b, another transcriptional target of p53, was up-regulated, the combination might turn out to be antagonistic. Mechanistically, miR-125b targeted BAK1 which was required for cisplatin sensitivity. Such in silico modeling exercises not only predicted synergism or antagonism, but also identified underlined drivers which could serve as biomarkers for desired therapeutic effects. The potential biomarkers identified by the network modeling approach could be used to guide selection of experimental system (e.g., cell line models) and monitor the combination effectiveness. The present study devised a mechanism to systematically capture microRNA information in regards to cancer drug resistance and established a computational framework to identify potential drug combinations to overcome resistance in cancer therapies.</jats:p> |
| container_issue |
10_Supplement |
| container_start_page |
0 |
| container_title |
Clinical Cancer Research |
| container_volume |
18 |
| format_de105 |
Article, E-Article |
| format_de14 |
Article, E-Article |
| format_de15 |
Article, E-Article |
| format_de520 |
Article, E-Article |
| format_de540 |
Article, E-Article |
| format_dech1 |
Article, E-Article |
| format_ded117 |
Article, E-Article |
| format_degla1 |
E-Article |
| format_del152 |
Buch |
| format_del189 |
Article, E-Article |
| format_dezi4 |
Article |
| format_dezwi2 |
Article, E-Article |
| format_finc |
Article, E-Article |
| format_nrw |
Article, E-Article |
| _version_ |
1792328348185133058 |
| geogr_code |
not assigned |
| last_indexed |
2024-03-01T12:51:27.882Z |
| geogr_code_person |
not assigned |
| openURL |
url_ver=Z39.88-2004&ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fvufind.svn.sourceforge.net%3Agenerator&rft.title=Abstract+B65%3A+MicroRNAs+in+cancer+drug+resistance+and+sensitivity&rft.date=2012-05-15&genre=article&issn=1557-3265&volume=18&issue=10_Supplement&pages=B65-B65&jtitle=Clinical+Cancer+Research&atitle=Abstract+B65%3A+MicroRNAs+in+cancer+drug+resistance+and+sensitivity&aulast=Zhu&aufirst=Jian&rft_id=info%3Adoi%2F10.1158%2F1078-0432.mechres-b65&rft.language%5B0%5D=eng |
| SOLR | |
| _version_ | 1792328348185133058 |
| author | Zhu, Jian |
| author_facet | Zhu, Jian, Zhu, Jian |
| author_sort | zhu, jian |
| container_issue | 10_Supplement |
| container_start_page | 0 |
| container_title | Clinical Cancer Research |
| container_volume | 18 |
| description | <jats:title>Abstract</jats:title> <jats:p>microRNAs are small noncoding RNAs of 18–25 nucleotides that have been shown to regulate gene expression posttranscriptionally and play fundamental roles in diverse biological and pathological processes. MiRNApedia is an in silico discovery tool designed to integrate all microRNA-related information including genetic variation, gene expression, epigenetic regulation, pathways, diseases, clinical outcomes and particularly drug actions. The system documented more than 1,000 microRNAs and 600 therapeutic and experimental compounds including well-known cancer drugs cisplatin, doxorubicin, 5-flouracil, gemicitabine, paclitaxel, docetaxal, imatinib, vorinostat, sorafenib and gefitinib etc. For each compound, microRNAs and genes related to its sensitivity and function were compiled from literature and used to construct comprehensive drug-gene-microRNA networks. MicroRNAs played important roles in determining resistance and sensitivity of cancer drugs. For example, miR-21 reduced sensitivities to daunorubicin, topotecan, 5-FU, taxol, doxorubicin, docetaxel, ara-C, arsenic trioxide, gemcitabine and dexamethasome, while miR-146a increased sensitivity to bleomycin and over-expression of miR-221 conferred resistance to tamoxifen. Multiple microRNAs might be involved in the efficacy of a single drug. MiRs -98, -214, -106a, -125b and -630 contributed to cisplatin resistance, while -451, -181a, -148a, -138 and let-7i enhanced its sensitivity. Meanwhile, cisplatin was shown to down-regulate miRs -150 and -106 while up-regulated miRs -34, -16, -17-5p and -125. Drug combination would be the choice to overcome resistance in mono-therapies. Prior to experimental testing, the combination effects of multiple drugs could be assessed computationally by combining annotated information in microRNA targets, signaling pathways and transcriptional regulations etc. For example, trichostatin A (TSA), a HDAC inhibitor, might enhance sensitivity of cisplatin by up-regulating p53 and its transcriptional target miR-34 which subsequently down-regulated BCL2, a well-known drug resistance factor. However, if miR-125b, another transcriptional target of p53, was up-regulated, the combination might turn out to be antagonistic. Mechanistically, miR-125b targeted BAK1 which was required for cisplatin sensitivity. Such in silico modeling exercises not only predicted synergism or antagonism, but also identified underlined drivers which could serve as biomarkers for desired therapeutic effects. The potential biomarkers identified by the network modeling approach could be used to guide selection of experimental system (e.g., cell line models) and monitor the combination effectiveness. The present study devised a mechanism to systematically capture microRNA information in regards to cancer drug resistance and established a computational framework to identify potential drug combinations to overcome resistance in cancer therapies.</jats:p> |
| doi_str_mv | 10.1158/1078-0432.mechres-b65 |
| facet_avail | Online, Free |
| finc_class_facet | Medizin |
| format | ElectronicArticle |
| format_de105 | Article, E-Article |
| format_de14 | Article, E-Article |
| format_de15 | Article, E-Article |
| format_de520 | Article, E-Article |
| format_de540 | Article, E-Article |
| format_dech1 | Article, E-Article |
| format_ded117 | Article, E-Article |
| format_degla1 | E-Article |
| format_del152 | Buch |
| format_del189 | Article, E-Article |
| format_dezi4 | Article |
| format_dezwi2 | Article, E-Article |
| format_finc | Article, E-Article |
| format_nrw | Article, E-Article |
| geogr_code | not assigned |
| geogr_code_person | not assigned |
| id | ai-49-aHR0cDovL2R4LmRvaS5vcmcvMTAuMTE1OC8xMDc4LTA0MzIubWVjaHJlcy1iNjU |
| imprint | American Association for Cancer Research (AACR), 2012 |
| imprint_str_mv | American Association for Cancer Research (AACR), 2012 |
| institution | DE-15, DE-Pl11, DE-Rs1, DE-14, DE-105, DE-Ch1, DE-L229, DE-D275, DE-Bn3, DE-Brt1, DE-Zwi2, DE-D161, DE-Zi4, DE-Gla1 |
| issn | 1078-0432, 1557-3265 |
| issn_str_mv | 1078-0432, 1557-3265 |
| language | English |
| last_indexed | 2024-03-01T12:51:27.882Z |
| match_str | zhu2012abstractb65micrornasincancerdrugresistanceandsensitivity |
| mega_collection | American Association for Cancer Research (AACR) (CrossRef) |
| physical | B65-B65 |
| publishDate | 2012 |
| publishDateSort | 2012 |
| publisher | American Association for Cancer Research (AACR) |
| record_format | ai |
| recordtype | ai |
| series | Clinical Cancer Research |
| source_id | 49 |
| spelling | Zhu, Jian 1078-0432 1557-3265 American Association for Cancer Research (AACR) Cancer Research Oncology http://dx.doi.org/10.1158/1078-0432.mechres-b65 <jats:title>Abstract</jats:title> <jats:p>microRNAs are small noncoding RNAs of 18–25 nucleotides that have been shown to regulate gene expression posttranscriptionally and play fundamental roles in diverse biological and pathological processes. MiRNApedia is an in silico discovery tool designed to integrate all microRNA-related information including genetic variation, gene expression, epigenetic regulation, pathways, diseases, clinical outcomes and particularly drug actions. The system documented more than 1,000 microRNAs and 600 therapeutic and experimental compounds including well-known cancer drugs cisplatin, doxorubicin, 5-flouracil, gemicitabine, paclitaxel, docetaxal, imatinib, vorinostat, sorafenib and gefitinib etc. For each compound, microRNAs and genes related to its sensitivity and function were compiled from literature and used to construct comprehensive drug-gene-microRNA networks. MicroRNAs played important roles in determining resistance and sensitivity of cancer drugs. For example, miR-21 reduced sensitivities to daunorubicin, topotecan, 5-FU, taxol, doxorubicin, docetaxel, ara-C, arsenic trioxide, gemcitabine and dexamethasome, while miR-146a increased sensitivity to bleomycin and over-expression of miR-221 conferred resistance to tamoxifen. Multiple microRNAs might be involved in the efficacy of a single drug. MiRs -98, -214, -106a, -125b and -630 contributed to cisplatin resistance, while -451, -181a, -148a, -138 and let-7i enhanced its sensitivity. Meanwhile, cisplatin was shown to down-regulate miRs -150 and -106 while up-regulated miRs -34, -16, -17-5p and -125. Drug combination would be the choice to overcome resistance in mono-therapies. Prior to experimental testing, the combination effects of multiple drugs could be assessed computationally by combining annotated information in microRNA targets, signaling pathways and transcriptional regulations etc. For example, trichostatin A (TSA), a HDAC inhibitor, might enhance sensitivity of cisplatin by up-regulating p53 and its transcriptional target miR-34 which subsequently down-regulated BCL2, a well-known drug resistance factor. However, if miR-125b, another transcriptional target of p53, was up-regulated, the combination might turn out to be antagonistic. Mechanistically, miR-125b targeted BAK1 which was required for cisplatin sensitivity. Such in silico modeling exercises not only predicted synergism or antagonism, but also identified underlined drivers which could serve as biomarkers for desired therapeutic effects. The potential biomarkers identified by the network modeling approach could be used to guide selection of experimental system (e.g., cell line models) and monitor the combination effectiveness. The present study devised a mechanism to systematically capture microRNA information in regards to cancer drug resistance and established a computational framework to identify potential drug combinations to overcome resistance in cancer therapies.</jats:p> Abstract B65: MicroRNAs in cancer drug resistance and sensitivity Clinical Cancer Research |
| spellingShingle | Zhu, Jian, Clinical Cancer Research, Abstract B65: MicroRNAs in cancer drug resistance and sensitivity, Cancer Research, Oncology |
| title | Abstract B65: MicroRNAs in cancer drug resistance and sensitivity |
| title_full | Abstract B65: MicroRNAs in cancer drug resistance and sensitivity |
| title_fullStr | Abstract B65: MicroRNAs in cancer drug resistance and sensitivity |
| title_full_unstemmed | Abstract B65: MicroRNAs in cancer drug resistance and sensitivity |
| title_short | Abstract B65: MicroRNAs in cancer drug resistance and sensitivity |
| title_sort | abstract b65: micrornas in cancer drug resistance and sensitivity |
| title_unstemmed | Abstract B65: MicroRNAs in cancer drug resistance and sensitivity |
| topic | Cancer Research, Oncology |
| url | http://dx.doi.org/10.1158/1078-0432.mechres-b65 |