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Abstract B21: Integrated genomic characterization of pancreatic ductal adenocarcinoma and the confounding role of purity

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Abstract We have utilized integrated genomic, transcriptomic and proteomic profiling to perform comprehensive molecular characterization of 150 pancreatic ductal adenocarcinoma (PAAD) specimens. PAAD demonstrates a characteristic biology notable for low neoplastic cellularity and prominent fibrotic stroma. Prior genome sequencing studies have focused on tumors with high neoplastic cellularity or have used physical techniques to enrich for tumor cell purity. Consequently, tumors with low neoplastic cellularity have been significantly underrepresented in existing genome sequencing efforts, even though they represent the majority of surgically resected PAAD samples. In a collaborative effort through The Cancer Genome Atlas (TCGA) network, we comprehensively analyzed 150 clinically annotated pancreatic cancers with a minimum of 1% neoplastic cellularity. We evaluated somatic DNA mutation and copy number alterations, mRNA and miRNA sequencing, and promoter methylation in all samples as well as proteomic profiles in a subset of tumors. We have overcome technical challenges of low neoplastic cellularity in primary tumors through deep whole exome and targeted gene panel sequencing to identify high-confidence somatic mutations in all samples, including 20 samples with less than 15% cellularity as assessed by ABSOLUTE. We observe recurrent somatic mutations in genes previously reported to be common in PAAD, including KRAS, TP53, SMAD4, and CDKN2A. We have observed copy number alterations in loci harboring the MYC, AKT2, and KRAS oncogenes and the CDKN2A tumor suppressor gene, among others. Moreover, we demonstrate two distinct classes of KRAS wild-type tumors based on the presence or absence of a RAS pathway genomic alteration. While low neoplastic cellularity was addressed through increased coverage with exome sequencing, other platforms were heavily influenced by purity, including mRNA, miRNA, RPPA and methylation. We find that, in our data, previously defined expression subtypes based on NMF-consensus clustering are highly confounded by purity, whereas recently published tumor-specific subtypes are purity-independent. Furthermore, we find that naïve approaches to defining molecular subtypes across each of our platforms resulted in defining groups of samples which were confounded with purity. Therefore, we divided our dataset by the median ABSOLUTE tumor purity, creating both a high- and low-purity classifications, and employed a two-stage approach to classifying the data. We first performed unsupervised clustering on higher-purity tumors and derived molecular classifiers that are more likely to reflect tumor cell biology, rather than that of the admixed stromal, immune and normal pancreas cells. We then projected these classifiers onto the larger dataset including both the high- and low-purity samples. We found that by pre-defining these tumor-specific discriminatory features that we were able to help mitigate the tendency of low purity samples to form their own groups, and instead define subtypes of disease which were not statistically significantly associated with tumor purity. Thus, we have used quantitative purity information to create and interpret methylation, copy number, mRNA and miRNA expression signatures as well as reverse phase protein array-based proteomic profiles which also have prognostic significance in an multivariate model. Finally, we observe multiple instances of predicted and observed methylation and miRNA regulation of RNA which help describe subtypes of disease. In summary, we have used our data, including miRNA and protein expression, to expand and help understand previous genomic and transcriptomic descriptions of PAAD. These data describe the molecular landscape of pancreatic cancer and may serve as a roadmap for future study of this disease. Citation Format: Richard A. Moffitt, on behalf of the Cancer Genome Atlas Research Network, The Cancer Genome Atlas Research Network.{Authors}. Integrated genomic characterization of pancreatic ductal adenocarcinoma and the confounding role of purity. [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2016 May 12-15; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(24 Suppl):Abstract nr B21.
American Association for Cancer Research (AACR)
Title: Abstract B21: Integrated genomic characterization of pancreatic ductal adenocarcinoma and the confounding role of purity
Description:
Abstract We have utilized integrated genomic, transcriptomic and proteomic profiling to perform comprehensive molecular characterization of 150 pancreatic ductal adenocarcinoma (PAAD) specimens.
PAAD demonstrates a characteristic biology notable for low neoplastic cellularity and prominent fibrotic stroma.
Prior genome sequencing studies have focused on tumors with high neoplastic cellularity or have used physical techniques to enrich for tumor cell purity.
Consequently, tumors with low neoplastic cellularity have been significantly underrepresented in existing genome sequencing efforts, even though they represent the majority of surgically resected PAAD samples.
In a collaborative effort through The Cancer Genome Atlas (TCGA) network, we comprehensively analyzed 150 clinically annotated pancreatic cancers with a minimum of 1% neoplastic cellularity.
We evaluated somatic DNA mutation and copy number alterations, mRNA and miRNA sequencing, and promoter methylation in all samples as well as proteomic profiles in a subset of tumors.
We have overcome technical challenges of low neoplastic cellularity in primary tumors through deep whole exome and targeted gene panel sequencing to identify high-confidence somatic mutations in all samples, including 20 samples with less than 15% cellularity as assessed by ABSOLUTE.
We observe recurrent somatic mutations in genes previously reported to be common in PAAD, including KRAS, TP53, SMAD4, and CDKN2A.
We have observed copy number alterations in loci harboring the MYC, AKT2, and KRAS oncogenes and the CDKN2A tumor suppressor gene, among others.
Moreover, we demonstrate two distinct classes of KRAS wild-type tumors based on the presence or absence of a RAS pathway genomic alteration.
While low neoplastic cellularity was addressed through increased coverage with exome sequencing, other platforms were heavily influenced by purity, including mRNA, miRNA, RPPA and methylation.
We find that, in our data, previously defined expression subtypes based on NMF-consensus clustering are highly confounded by purity, whereas recently published tumor-specific subtypes are purity-independent.
Furthermore, we find that naïve approaches to defining molecular subtypes across each of our platforms resulted in defining groups of samples which were confounded with purity.
Therefore, we divided our dataset by the median ABSOLUTE tumor purity, creating both a high- and low-purity classifications, and employed a two-stage approach to classifying the data.
We first performed unsupervised clustering on higher-purity tumors and derived molecular classifiers that are more likely to reflect tumor cell biology, rather than that of the admixed stromal, immune and normal pancreas cells.
We then projected these classifiers onto the larger dataset including both the high- and low-purity samples.
We found that by pre-defining these tumor-specific discriminatory features that we were able to help mitigate the tendency of low purity samples to form their own groups, and instead define subtypes of disease which were not statistically significantly associated with tumor purity.
Thus, we have used quantitative purity information to create and interpret methylation, copy number, mRNA and miRNA expression signatures as well as reverse phase protein array-based proteomic profiles which also have prognostic significance in an multivariate model.
Finally, we observe multiple instances of predicted and observed methylation and miRNA regulation of RNA which help describe subtypes of disease.
In summary, we have used our data, including miRNA and protein expression, to expand and help understand previous genomic and transcriptomic descriptions of PAAD.
These data describe the molecular landscape of pancreatic cancer and may serve as a roadmap for future study of this disease.
Citation Format: Richard A.
Moffitt, on behalf of the Cancer Genome Atlas Research Network, The Cancer Genome Atlas Research Network.
{Authors}.
Integrated genomic characterization of pancreatic ductal adenocarcinoma and the confounding role of purity.
[abstract].
In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2016 May 12-15; Orlando, FL.
Philadelphia (PA): AACR; Cancer Res 2016;76(24 Suppl):Abstract nr B21.

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