Limits...
An integrated model of the transcriptome of HER2-positive breast cancer.

Kalari KR, Necela BM, Tang X, Thompson KJ, Lau M, Eckel-Passow JE, Kachergus JM, Anderson SK, Sun Z, Baheti S, Carr JM, Baker TR, Barman P, Radisky DC, Joseph RW, McLaughlin SA, Chai HS, Camille S, Rossell D, Asmann YW, Thompson EA, Perez EA - PLoS ONE (2013)

Bottom Line: We interrogated RNA-Seq data from benign breast lesions, ER+, triple negative, and HER2-positive tumors to identify 685 differentially expressed genes, 102 alternatively spliced genes, and 303 genes that expressed single nucleotide sequence variants (eSNVs) that were associated with the HER2-positive tumors in our survey panel.These features were integrated into a transcriptome landscape model that identified 12 highly interconnected genomic modules, each of which represents a cellular processes pathway that appears to define the genomic architecture of the HER2-positive tumors in our test set.These data indicate that an integrated transcriptome landscape model derived from a test set of HER2-positive breast tumors has potential for predicting outcome and for identifying novel potential therapeutic strategies for this breast cancer subtype.

View Article: PubMed Central - PubMed

Affiliation: Department of Cancer Biology, Mayo Clinic, Jacksonville, Florida, United States of America ; Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, United States of America.

ABSTRACT
Our goal in these analyses was to use genomic features from a test set of primary breast tumors to build an integrated transcriptome landscape model that makes relevant hypothetical predictions about the biological and/or clinical behavior of HER2-positive breast cancer. We interrogated RNA-Seq data from benign breast lesions, ER+, triple negative, and HER2-positive tumors to identify 685 differentially expressed genes, 102 alternatively spliced genes, and 303 genes that expressed single nucleotide sequence variants (eSNVs) that were associated with the HER2-positive tumors in our survey panel. These features were integrated into a transcriptome landscape model that identified 12 highly interconnected genomic modules, each of which represents a cellular processes pathway that appears to define the genomic architecture of the HER2-positive tumors in our test set. The generality of the model was confirmed by the observation that several key pathways were enriched in HER2-positive TCGA breast tumors. The ability of this model to make relevant predictions about the biology of breast cancer cells was established by the observation that integrin signaling was linked to lapatinib sensitivity in vitro and strongly associated with risk of relapse in the NCCTG N9831 adjuvant trastuzumab clinical trial dataset. Additional modules from the HER2 transcriptome model, including ubiquitin-mediated proteolysis, TGF-beta signaling, RHO-family GTPase signaling, and M-phase progression, were linked to response to lapatinib and paclitaxel in vitro and/or risk of relapse in the N9831 dataset. These data indicate that an integrated transcriptome landscape model derived from a test set of HER2-positive breast tumors has potential for predicting outcome and for identifying novel potential therapeutic strategies for this breast cancer subtype.

Show MeSH

Related in: MedlinePlus

Visualization of single nucleotide variant validation.Sanger sequence validation of highly expressed novel somatic SNVs for MRPL3 variant in the BCT40 HER2 tumor sample. RNA-Seq sequence reads shown above Sanger sequencing tracing, with mutation shown by an arrow.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3815156&req=5

pone-0079298-g007: Visualization of single nucleotide variant validation.Sanger sequence validation of highly expressed novel somatic SNVs for MRPL3 variant in the BCT40 HER2 tumor sample. RNA-Seq sequence reads shown above Sanger sequencing tracing, with mutation shown by an arrow.

Mentions: Sanger sequence chromatograms for two validated somatic mutations are shown in Figures 7 and 8 to illustrate the range of allelic frequencies that we commonly observed. MRPL3 was nominated in tumor BCT40 as a C to G variant on chromosome 3 at coordinates 131220447 (chromosome 3: 131220447) with 53 reads supporting the reference allele (C) and 79 reads supporting the alternate allele (G). Sanger sequence analysis (Figure 7) confirmed this as a heterozygous D69H (chromosome 3: 131220447) somatic mutation. In contrast, the gene encoding transcription factor FOXA1 was called as a C to T variant (chromosome 14:38061115) with 4 reference allele reads and 6 alternate allele reads. Although this variant was confirmed as a somatic mutation by Sanger sequence analysis (Figure 8), the variant allele appears to be present in less than half of the alleles in tumor genomic DNA. This observation informs our strong supposition that RNA-Seq is a very sensitive tool for detecting eSNVs that are expressed in a subset of tumor cells.


An integrated model of the transcriptome of HER2-positive breast cancer.

Kalari KR, Necela BM, Tang X, Thompson KJ, Lau M, Eckel-Passow JE, Kachergus JM, Anderson SK, Sun Z, Baheti S, Carr JM, Baker TR, Barman P, Radisky DC, Joseph RW, McLaughlin SA, Chai HS, Camille S, Rossell D, Asmann YW, Thompson EA, Perez EA - PLoS ONE (2013)

Visualization of single nucleotide variant validation.Sanger sequence validation of highly expressed novel somatic SNVs for MRPL3 variant in the BCT40 HER2 tumor sample. RNA-Seq sequence reads shown above Sanger sequencing tracing, with mutation shown by an arrow.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3815156&req=5

pone-0079298-g007: Visualization of single nucleotide variant validation.Sanger sequence validation of highly expressed novel somatic SNVs for MRPL3 variant in the BCT40 HER2 tumor sample. RNA-Seq sequence reads shown above Sanger sequencing tracing, with mutation shown by an arrow.
Mentions: Sanger sequence chromatograms for two validated somatic mutations are shown in Figures 7 and 8 to illustrate the range of allelic frequencies that we commonly observed. MRPL3 was nominated in tumor BCT40 as a C to G variant on chromosome 3 at coordinates 131220447 (chromosome 3: 131220447) with 53 reads supporting the reference allele (C) and 79 reads supporting the alternate allele (G). Sanger sequence analysis (Figure 7) confirmed this as a heterozygous D69H (chromosome 3: 131220447) somatic mutation. In contrast, the gene encoding transcription factor FOXA1 was called as a C to T variant (chromosome 14:38061115) with 4 reference allele reads and 6 alternate allele reads. Although this variant was confirmed as a somatic mutation by Sanger sequence analysis (Figure 8), the variant allele appears to be present in less than half of the alleles in tumor genomic DNA. This observation informs our strong supposition that RNA-Seq is a very sensitive tool for detecting eSNVs that are expressed in a subset of tumor cells.

Bottom Line: We interrogated RNA-Seq data from benign breast lesions, ER+, triple negative, and HER2-positive tumors to identify 685 differentially expressed genes, 102 alternatively spliced genes, and 303 genes that expressed single nucleotide sequence variants (eSNVs) that were associated with the HER2-positive tumors in our survey panel.These features were integrated into a transcriptome landscape model that identified 12 highly interconnected genomic modules, each of which represents a cellular processes pathway that appears to define the genomic architecture of the HER2-positive tumors in our test set.These data indicate that an integrated transcriptome landscape model derived from a test set of HER2-positive breast tumors has potential for predicting outcome and for identifying novel potential therapeutic strategies for this breast cancer subtype.

View Article: PubMed Central - PubMed

Affiliation: Department of Cancer Biology, Mayo Clinic, Jacksonville, Florida, United States of America ; Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, United States of America.

ABSTRACT
Our goal in these analyses was to use genomic features from a test set of primary breast tumors to build an integrated transcriptome landscape model that makes relevant hypothetical predictions about the biological and/or clinical behavior of HER2-positive breast cancer. We interrogated RNA-Seq data from benign breast lesions, ER+, triple negative, and HER2-positive tumors to identify 685 differentially expressed genes, 102 alternatively spliced genes, and 303 genes that expressed single nucleotide sequence variants (eSNVs) that were associated with the HER2-positive tumors in our survey panel. These features were integrated into a transcriptome landscape model that identified 12 highly interconnected genomic modules, each of which represents a cellular processes pathway that appears to define the genomic architecture of the HER2-positive tumors in our test set. The generality of the model was confirmed by the observation that several key pathways were enriched in HER2-positive TCGA breast tumors. The ability of this model to make relevant predictions about the biology of breast cancer cells was established by the observation that integrin signaling was linked to lapatinib sensitivity in vitro and strongly associated with risk of relapse in the NCCTG N9831 adjuvant trastuzumab clinical trial dataset. Additional modules from the HER2 transcriptome model, including ubiquitin-mediated proteolysis, TGF-beta signaling, RHO-family GTPase signaling, and M-phase progression, were linked to response to lapatinib and paclitaxel in vitro and/or risk of relapse in the N9831 dataset. These data indicate that an integrated transcriptome landscape model derived from a test set of HER2-positive breast tumors has potential for predicting outcome and for identifying novel potential therapeutic strategies for this breast cancer subtype.

Show MeSH
Related in: MedlinePlus