Systematic Assessment of Tumor Purity and Its Clinical Implications

The tumor microenvironment is complex, comprising heterogeneous cellular populations. As molecular profiles are frequently generated using bulk tissue sections, they represent an admixture of multiple cell types (including immune, stromal, and cancer cells) interacting with each other. Therefore, th...

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Published inJCO precision oncology Vol. 4
Main Authors Haider, Syed, Tyekucheva, Svitlana, Prandi, Davide, Fox, Natalie S, Ahn, Jaeil, Xu, Andrew Wei, Pantazi, Angeliki, Park, Peter J, Laird, Peter W, Sander, Chris, Wang, Wenyi, Demichelis, Francesca, Loda, Massimo, Boutros, Paul C
Format Journal Article
LanguageEnglish
Published United States 04.09.2020
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Abstract The tumor microenvironment is complex, comprising heterogeneous cellular populations. As molecular profiles are frequently generated using bulk tissue sections, they represent an admixture of multiple cell types (including immune, stromal, and cancer cells) interacting with each other. Therefore, these molecular profiles are confounded by signals emanating from many cell types. Accurate assessment of residual cancer cell fraction is crucial for parameterization and interpretation of genomic analyses, as well as for accurately interpreting the clinical properties of the tumor. To benchmark cancer cell fraction estimation methods, 10 estimators were applied to a clinical cohort of 333 patients with prostate cancer. These methods include gold-standard multiobserver pathology estimates, as well as estimates inferred from genome, epigenome, and transcriptome data. In addition, two methods based on genomic and transcriptomic profiles were used to quantify tumor purity in 4,497 tumors across 12 cancer types. Bulk mRNA and microRNA profiles were subject to in silico deconvolution to estimate cancer cell-specific mRNA and microRNA profiles. We present a systematic comparison of 10 tumor purity estimation methods on a cohort of 333 prostate tumors. We quantify variation among purity estimation methods and demonstrate how this influences interpretation of clinico-genomic analyses. Our data show poor concordance between pathologic and molecular purity estimates, necessitating caution when interpreting molecular results. Limited concordance between DNA- and mRNA-derived purity estimates remained a general pan-cancer phenomenon when tested in an additional 4,497 tumors spanning 12 cancer types. The choice of tumor purity estimation method may have a profound impact on the interpretation of genomic assays. Taken together, these data highlight the need for improved assessment of tumor purity and quantitation of its influences on the molecular hallmarks of cancers.
AbstractList The tumor microenvironment is complex, comprising heterogeneous cellular populations. As molecular profiles are frequently generated using bulk tissue sections, they represent an admixture of multiple cell types (including immune, stromal, and cancer cells) interacting with each other. Therefore, these molecular profiles are confounded by signals emanating from many cell types. Accurate assessment of residual cancer cell fraction is crucial for parameterization and interpretation of genomic analyses, as well as for accurately interpreting the clinical properties of the tumor. To benchmark cancer cell fraction estimation methods, 10 estimators were applied to a clinical cohort of 333 patients with prostate cancer. These methods include gold-standard multiobserver pathology estimates, as well as estimates inferred from genome, epigenome, and transcriptome data. In addition, two methods based on genomic and transcriptomic profiles were used to quantify tumor purity in 4,497 tumors across 12 cancer types. Bulk mRNA and microRNA profiles were subject to in silico deconvolution to estimate cancer cell-specific mRNA and microRNA profiles. We present a systematic comparison of 10 tumor purity estimation methods on a cohort of 333 prostate tumors. We quantify variation among purity estimation methods and demonstrate how this influences interpretation of clinico-genomic analyses. Our data show poor concordance between pathologic and molecular purity estimates, necessitating caution when interpreting molecular results. Limited concordance between DNA- and mRNA-derived purity estimates remained a general pan-cancer phenomenon when tested in an additional 4,497 tumors spanning 12 cancer types. The choice of tumor purity estimation method may have a profound impact on the interpretation of genomic assays. Taken together, these data highlight the need for improved assessment of tumor purity and quantitation of its influences on the molecular hallmarks of cancers.
Author Laird, Peter W
Sander, Chris
Xu, Andrew Wei
Demichelis, Francesca
Fox, Natalie S
Prandi, Davide
Park, Peter J
Loda, Massimo
Wang, Wenyi
Haider, Syed
Tyekucheva, Svitlana
Ahn, Jaeil
Pantazi, Angeliki
Boutros, Paul C
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  organization: The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, United Kingdom
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  givenname: Svitlana
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  organization: Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
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  surname: Prandi
  fullname: Prandi, Davide
  organization: Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy
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  fullname: Fox, Natalie S
  organization: Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
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  surname: Ahn
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  organization: Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University Medical Center, Washington, DC
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  organization: Brigham and Women's Hospital, Boston, MA
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  organization: Department of Biomedical Informatics, Harvard Medical School, Boston, MA
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  organization: Van Andel Research Institute, Grand Rapids, MI
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  organization: Department of Cell Biology, Harvard Medical School, Boston, MA
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  organization: The University of Texas MD Anderson Cancer Center Department of Bioinformatics and Computational Biology, Houston
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  givenname: Francesca
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  organization: Englander Institute for Precision Medicine, New York Presbyterian Hospital, Weill Cornell Medicine, New York, NY
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  surname: Loda
  fullname: Loda, Massimo
  organization: Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, MA
– sequence: 14
  givenname: Paul C
  surname: Boutros
  fullname: Boutros, Paul C
  organization: Institute for Precision Health, University of California, Los Angeles, CA
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