Dataset Information

MicroRNAs as possible indicators of drug sensitivity in breast cancer cell lines.

ABSTRACT: MicroRNAs (miRNAs) regulate gene expression post-transcriptionally. In this way they might influence whether a cell is sensitive or resistant to a certain drug. So far, only a limited number of relatively small scale studies comprising few cell lines and/or drugs have been performed. To obtain a broader view on miRNAs and their association with drug response, we investigated the expression levels of 411 miRNAs in relation to drug sensitivity in 36 breast cancer cell lines. For this purpose IC50 values of a drug screen involving 34 drugs were associated with miRNA expression data of the same breast cancer cell lines. Since molecular subtype of the breast cancer cell lines is considered a confounding factor in drug association studies, multivariate analysis taking subtype into account was performed on significant miRNA-drug associations which retained 13 associations. These associations consisted of 11 different miRNAs and eight different drugs (among which Paclitaxel, Docetaxel and Veliparib). The taxanes, Paclitaxel and Docetaxel, were the only drugs having miRNAs in common: hsa-miR-187-5p and hsa-miR-106a-3p indicative of drug resistance while Paclitaxel sensitivity alone associated with hsa-miR-556-5p. Tivantinib was associated with hsa-let-7d-5p and hsa-miR-18a-5p for sensitivity and hsa-miR-637 for resistance. Drug sensitivity was associated with hsa-let-7a-5p for Bortezomib, hsa-miR-135a-3p for JNJ-707 and hsa-miR-185-3p for Panobinostat. Drug resistance was associated with hsa-miR-182-5p for Veliparib and hsa-miR-629-5p for Tipifarnib. Pathway analysis for significant miRNAs was performed to reveal biological roles, aiding to find a potential mechanistic link for the observed associations with drug response. By doing so hsa-miR-187-5p was linked to the cell cycle G2-M checkpoint in line with this checkpoint being the target of taxanes. In conclusion, our study shows that miRNAs could potentially serve as biomarkers for intrinsic drug resistance and that pathway analyses can provide additional information in this context.

SUBMITTER: Uhr K

PROVIDER: S-EPMC6504094 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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MicroRNAs as possible indicators of drug sensitivity in breast cancer cell lines.

Uhr Katharina K Prager-van der Smissen Wendy J C WJC Heine Anouk A J AAJ Ozturk Bahar B van Jaarsveld Marijn T M MTM Boersma Antonius W M AWM Jager Agnes A Wiemer Erik A C EAC Smid Marcel M Foekens John A JA Martens John W M JWM

PloS one 20190507 5

MicroRNAs (miRNAs) regulate gene expression post-transcriptionally. In this way they might influence whether a cell is sensitive or resistant to a certain drug. So far, only a limited number of relatively small scale studies comprising few cell lines and/or drugs have been performed. To obtain a broader view on miRNAs and their association with drug response, we investigated the expression levels of 411 miRNAs in relation to drug sensitivity in 36 breast cancer cell lines. For this purpose IC50 ...[more]

PMID: 31063487

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Project description:BackgroundRecent landmark studies have profiled cancer cell lines for molecular features, along with measuring the corresponding growth inhibitory effects for specific drug compounds. These data present a tool for determining which subsets of human cancer might be more responsive to particular drugs. To this end, the NCI-DREAM-sponsored DREAM7: Drug Sensitivity Prediction Challenge (sub-challenge 1) set out to predict the sensitivities of 18 breast cancer cell lines to 31 previously untested compounds, on the basis of molecular profiling data and a training subset of cell lines.Methods and resultsWith 47 teams submitting blinded predictions, team Creighton scored third in terms of overall accuracy. Team Creighton's method was simple and straightforward, incorporated multiple expression data types (RNA-seq, gene array, RPPA), and incorporated all profiled features (not only the "best" predictive ones). As an extension of the approach, cell line data, from public datasets of expression profiling coupled with drug sensitivities (Barretina, Garnett, Heiser) were used to "predict" the drug sensitivities in human breast tumors (using data from The Cancer Genome Atlas). Drug sensitivity correlations within human breast tumors showed differences by expression-based subtype, with many associations in line with the expected (e.g. Lapatinib sensitivity in HER2-enriched cancers) and others inviting further study (e.g. relative resistance to PI3K inhibitors in basal-like cancers).ConclusionsMolecular patterns associated with drug sensitivity are widespread, with potentially hundreds of genes that could be incorporated into making predictions, as well as offering biological clues as to the mechanisms involved. Applying the cell line patterns to human tumor data may help generate hypotheses on what tumor subsets might be more responsive to therapies, where multiple cell line datasets representing various drugs may be used, in order to assess consistency of patterns.

Project description:A hypermethylation defect associated with DNMT hyperactivity and DNMT3b overexpression characterizes a subset of breast cancers and breast cancer cell lines. We analyzed breast cancer cell lines for differential expression of regulatory miRs to determine if loss of miR-mediated post-transcriptional regulation of DNMT3b represents the molecular mechanism that governs the overexpression of DNMT3b that drives the hypermethylation defect in breast cancer. MicroRNAs (miRs) that regulate (miR-29a, miR-29b, miR-29c, miR-148a, miR-148b) or are predicted (miR-26a, miR-26b, miR-203, miR-222) to regulate DNMT3b were examined among 10 hypermethylator and 6 non-hypermethylator breast cancer cell lines. Hypermethylator cell lines express diminished levels of miR-29c, miR-148a, miR-148b, miR-26a, miR-26b, and miR-203 compared to non-hypermethylator cell lines. miR expression patterns correlate inversely with methylation-sensitive gene expression (r=-0.66, p=0.0056) and directly with the methylation status of these genes (r=0.72, p=0.002). To determine the mechanistic role of specific miRs in the dysregulation of DNMT3b among breast cancer cell lines, miR levels were modulated by transfection of pre-miR precursors for miR-148b, miR-26b, and miR-29c into hypermethylator cell lines (Hs578T, HCC1937, SUM185) and transfection of antagomirs directed against miR-148b, miR-26b, and miR-29c into non-hypermethylator cell lines (BT20, MDA-MB-415, MDA-MB-468). Antagomir-mediated knock-down of miR-148b, miR-29c, and miR-26b significantly increased DNMT3b mRNA in non-hypermethylator cell lines, and re-expression of miR-148b, miR-29c, and miR-26b following transfection of pre-miR precursors significantly reduced DNMT3b mRNA in hypermethylator cell lines. These findings strongly suggest that: i) post-transcriptional regulation of DNMT3b is combinatorial, ii) diminished expression of regulatory miRs contributes to DNMT3b overexpression, iii) re-expression of regulatory miRs reduces DNMT3b mRNA levels in hypermethylator breast cancer cell lines, and iv) down-regulation of regulatory miRs increases DNMT3b mRNA levels in non-hypermethylator breast cancer cell lines. In conlcusion, the molecular mechanism governing the DNMT3b-mediated hypermethylation defect in breast cancer cell lines involves the loss of post-transcriptional regulation of DNMT3b by regulatory miRs.

Project description:Understanding the heterogeneous drug response of cancer patients is essential to precision oncology. Pioneering genomic analyses of individual cancer subtypes have begun to identify key determinants of resistance, including up-regulation of multi-drug resistance (MDR) genes and mutational alterations of drug targets. However, these alterations are sufficient to explain only a minority of the population, and additional mechanisms of drug resistance or sensitivity are required to explain the remaining spectrum of patient responses to ultimately achieve the goal of precision oncology. We hypothesized that a pan-cancer analysis of in vitro drug sensitivities across numerous cancer lineages will improve the detection of statistical associations and yield more robust and, importantly, recurrent determinants of response. In this study, we developed a statistical framework based on the meta-analysis of expression profiles to identify pan-cancer markers and mechanisms of drug response. Using the Cancer Cell Line Encyclopaedia (CCLE), a large panel of several hundred cancer cell lines from numerous distinct lineages, we characterized both known and novel mechanisms of response to cytotoxic drugs including inhibitors of Topoisomerase 1 (TOP1; Topotecan, Irinotecan) and targeted therapies including inhibitors of histone deacetylases (HDAC; Panobinostat) and MAP/ERK kinases (MEK; PD-0325901, AZD6244). Notably, our analysis implicated reduced replication and transcriptional rates, as well as deficiency in DNA damage repair genes in resistance to TOP1 inhibitors. The constitutive activation of several signaling pathways including the interferon/STAT-1 pathway was implicated in resistance to the pan-HDAC inhibitor. Finally, a number of dysregulations upstream of MEK were identified as compensatory mechanisms of resistance to the MEK inhibitors. In comparison to alternative pan-cancer analysis strategies, our approach can better elucidate relevant drug response mechanisms. Moreover, the compendium of putative markers and mechanisms identified through our analysis can serve as a foundation for future studies into these drugs.

Dataset Information

MicroRNAs as possible indicators of drug sensitivity in breast cancer cell lines.

Publications

MicroRNAs as possible indicators of drug sensitivity in breast cancer cell lines.

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