Limits...
mRNA profiling reveals determinants of trastuzumab efficiency in HER2-positive breast cancer.

von der Heyde S, Wagner S, Czerny A, Nietert M, Ludewig F, Salinas-Riester G, Arlt D, Beißbarth T - PLoS ONE (2015)

Bottom Line: ALPP, CALCOCO1, CAV1, CYP1A2 and IGFBP3 were significantly higher expressed in the trastuzumab treated than in the untreated BT474 cell line.GDF15, IL8, LCN2, PTGS2 and 20 other genes were significantly higher expressed in HCC1954 than in BT474, while NCAM2, COLEC12, AFF3, TFF3, NRCAM, GREB1 and TFF1 were significantly lower expressed.These results contribute to a better understanding of trastuzumab action and resistance mechanisms.

View Article: PubMed Central - PubMed

Affiliation: Statistical Bioinformatics, Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany; IndivuTest GmbH, Hamburg, Germany.

ABSTRACT
Intrinsic and acquired resistance to the monoclonal antibody drug trastuzumab is a major problem in the treatment of HER2-positive breast cancer. A deeper understanding of the underlying mechanisms could help to develop new agents. Our intention was to detect genes and single nucleotide polymorphisms (SNPs) affecting trastuzumab efficiency in cell culture. Three HER2-positive breast cancer cell lines with different resistance phenotypes were analyzed. We chose BT474 as model of trastuzumab sensitivity, HCC1954 as model of intrinsic resistance, and BTR50, derived from BT474, as model of acquired resistance. Based on RNA-Seq data, we performed differential expression analyses on these cell lines with and without trastuzumab treatment. Differentially expressed genes between the resistant cell lines and BT474 are expected to contribute to resistance. Differentially expressed genes between untreated and trastuzumab treated BT474 are expected to contribute to drug efficacy. To exclude false positives from the candidate gene set, we removed genes that were also differentially expressed between untreated and trastuzumab treated BTR50. We further searched for SNPs in the untreated cell lines which could contribute to trastuzumab resistance. The analysis resulted in 54 differentially expressed candidate genes that might be connected to trastuzumab efficiency. 90% of 40 selected candidates were validated by RT-qPCR. ALPP, CALCOCO1, CAV1, CYP1A2 and IGFBP3 were significantly higher expressed in the trastuzumab treated than in the untreated BT474 cell line. GDF15, IL8, LCN2, PTGS2 and 20 other genes were significantly higher expressed in HCC1954 than in BT474, while NCAM2, COLEC12, AFF3, TFF3, NRCAM, GREB1 and TFF1 were significantly lower expressed. Additionally, we inferred SNPs in HCC1954 for CAV1, PTGS2, IL8 and IGFBP3. The latter also had a variation in BTR50. 20% of the validated subset have already been mentioned in literature. For half of them we called and analyzed SNPs. These results contribute to a better understanding of trastuzumab action and resistance mechanisms.

Show MeSH

Related in: MedlinePlus

Fold Changes of DE genes (BT474 plus trastuzumab vs. BT474).The barchart displays the log2 fold changes of validated candidate genes, which significantly changed their expression in BT474 after trastuzumab treatment. The positive values indicate an upregulation upon drug treatment. Black bars denote values resulting from RNA-Seq analysis. Gray bars denote values resulting from RT-qPCR analysis.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4339844&req=5

pone.0117818.g003: Fold Changes of DE genes (BT474 plus trastuzumab vs. BT474).The barchart displays the log2 fold changes of validated candidate genes, which significantly changed their expression in BT474 after trastuzumab treatment. The positive values indicate an upregulation upon drug treatment. Black bars denote values resulting from RNA-Seq analysis. Gray bars denote values resulting from RT-qPCR analysis.

Mentions: The validated candidate genes ALPP, CYP1A2, CAV1, IGFBP3 and CALCOCO1 had positive log2 fold changes (FC) indicating an upregulation in BT474 when treated with trastuzumab. Fig. 3 shows the log2 FC resulting from RNA-Seq and RT-qPCR analysis, respectively. Table 1 lists the gene descriptions as well as the log2 FC and fdr of the RNA-Seq analysis. It is an excerpt of S3 Table.


mRNA profiling reveals determinants of trastuzumab efficiency in HER2-positive breast cancer.

von der Heyde S, Wagner S, Czerny A, Nietert M, Ludewig F, Salinas-Riester G, Arlt D, Beißbarth T - PLoS ONE (2015)

Fold Changes of DE genes (BT474 plus trastuzumab vs. BT474).The barchart displays the log2 fold changes of validated candidate genes, which significantly changed their expression in BT474 after trastuzumab treatment. The positive values indicate an upregulation upon drug treatment. Black bars denote values resulting from RNA-Seq analysis. Gray bars denote values resulting from RT-qPCR analysis.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4339844&req=5

pone.0117818.g003: Fold Changes of DE genes (BT474 plus trastuzumab vs. BT474).The barchart displays the log2 fold changes of validated candidate genes, which significantly changed their expression in BT474 after trastuzumab treatment. The positive values indicate an upregulation upon drug treatment. Black bars denote values resulting from RNA-Seq analysis. Gray bars denote values resulting from RT-qPCR analysis.
Mentions: The validated candidate genes ALPP, CYP1A2, CAV1, IGFBP3 and CALCOCO1 had positive log2 fold changes (FC) indicating an upregulation in BT474 when treated with trastuzumab. Fig. 3 shows the log2 FC resulting from RNA-Seq and RT-qPCR analysis, respectively. Table 1 lists the gene descriptions as well as the log2 FC and fdr of the RNA-Seq analysis. It is an excerpt of S3 Table.

Bottom Line: ALPP, CALCOCO1, CAV1, CYP1A2 and IGFBP3 were significantly higher expressed in the trastuzumab treated than in the untreated BT474 cell line.GDF15, IL8, LCN2, PTGS2 and 20 other genes were significantly higher expressed in HCC1954 than in BT474, while NCAM2, COLEC12, AFF3, TFF3, NRCAM, GREB1 and TFF1 were significantly lower expressed.These results contribute to a better understanding of trastuzumab action and resistance mechanisms.

View Article: PubMed Central - PubMed

Affiliation: Statistical Bioinformatics, Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany; IndivuTest GmbH, Hamburg, Germany.

ABSTRACT
Intrinsic and acquired resistance to the monoclonal antibody drug trastuzumab is a major problem in the treatment of HER2-positive breast cancer. A deeper understanding of the underlying mechanisms could help to develop new agents. Our intention was to detect genes and single nucleotide polymorphisms (SNPs) affecting trastuzumab efficiency in cell culture. Three HER2-positive breast cancer cell lines with different resistance phenotypes were analyzed. We chose BT474 as model of trastuzumab sensitivity, HCC1954 as model of intrinsic resistance, and BTR50, derived from BT474, as model of acquired resistance. Based on RNA-Seq data, we performed differential expression analyses on these cell lines with and without trastuzumab treatment. Differentially expressed genes between the resistant cell lines and BT474 are expected to contribute to resistance. Differentially expressed genes between untreated and trastuzumab treated BT474 are expected to contribute to drug efficacy. To exclude false positives from the candidate gene set, we removed genes that were also differentially expressed between untreated and trastuzumab treated BTR50. We further searched for SNPs in the untreated cell lines which could contribute to trastuzumab resistance. The analysis resulted in 54 differentially expressed candidate genes that might be connected to trastuzumab efficiency. 90% of 40 selected candidates were validated by RT-qPCR. ALPP, CALCOCO1, CAV1, CYP1A2 and IGFBP3 were significantly higher expressed in the trastuzumab treated than in the untreated BT474 cell line. GDF15, IL8, LCN2, PTGS2 and 20 other genes were significantly higher expressed in HCC1954 than in BT474, while NCAM2, COLEC12, AFF3, TFF3, NRCAM, GREB1 and TFF1 were significantly lower expressed. Additionally, we inferred SNPs in HCC1954 for CAV1, PTGS2, IL8 and IGFBP3. The latter also had a variation in BTR50. 20% of the validated subset have already been mentioned in literature. For half of them we called and analyzed SNPs. These results contribute to a better understanding of trastuzumab action and resistance mechanisms.

Show MeSH
Related in: MedlinePlus