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Title: Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

Abstract

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and post-treatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution.

Authors:
 [1];  [2];  [3];  [4];  [5];  [6];  [6];  [6];  [7];  [8];  [9];  [9];  [5];  [10];  [11];  [12];  [13];  [6];  [14];  [2] more »;  [15] « less
+ Show Author Affiliations
  1. Dana-Farber Cancer Institute, Boston, MA (United States); Brigham and Women's Hospital, Boston, MA (United States); Harvard Medical School, Boston, MA (United States); Institut d'Investigacions Biomediques, Barcelona (Spain)
  2. Dana-Farber Cancer Institute, Boston, MA (United States); Harvard School of Public Health, Boston, MA (United States)
  3. Dana-Farber Cancer Institute, Boston, MA (United States); Harvard School of Public Health, Boston, MA (United States); Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  4. MIT (Massachusetts Inst. of Technology), Cambridge, MA (United States); Weizmann Institute of Science, Rehovot (Israel)
  5. Dana-Farber Cancer Institute, Boston, MA (United States); Brigham and Women's Hospital, Boston, MA (United States); Harvard Medical School, Boston, MA (United States)
  6. Institut d'Investigacions Biomediques, Barcelona (Spain)
  7. Oslo Univ. Hospital Radiumhospitalet, Oslo (Norway); Univ. of Oslo, Oslo (Norway); Oslo Univ. Hospital, Oslo (Norway)
  8. Oslo Univ. Hospital Radiumhospitalet, Oslo (Norway); Oslo Univ. Hospital, Oslo (Norway); Univ. of Oslo, Oslo (Norway)
  9. Oslo Univ. Hospital Radiumhospitalet, Oslo (Norway); Univ. of Oslo, Oslo (Norway)
  10. MIT (Massachusetts Inst. of Technology), Cambridge, MA (United States); Royal Netherlands Academy of Arts and Sciences and Univ. Medical Center Utrecht, Utrecht (The Netherlands)
  11. The Royal Marsden Hospital, London (United Kingdom)
  12. The Royal Marsden Hospital, London (United Kingdom); Seattle Cancer Care Alliance, Seattle, WA (United States)
  13. The Royal Marsden Hospital, London (United Kingdom); Memorial Sloan-Kettering Cancer Center, New York, NY (United States)
  14. Memorial Sloan-Kettering Cancer Center, New York, NY (United States)
  15. Dana-Farber Cancer Institute, Boston, MA (United States); Brigham and Women's Hospital, Boston, MA (United States); Harvard Medical School, Boston, MA (United States); Harvard Stem Cell Institute, Cambridge, MA (United States); Broad Institute, Cambridge, MA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1201672
Resource Type:
Accepted Manuscript
Journal Name:
Cell Reports
Additional Journal Information:
Journal Volume: 6; Journal Issue: 3; Journal ID: ISSN 2211-1247
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE

Citation Formats

Almendro, Vanessa, Cheng, Yu -Kang, Randles, Amanda, Itzkovitz, Shalev, Marusyk, Andriy, Ametller, Elisabet, Gonzalez-Farre, Xavier, Muñoz, Montse, Russnes, Hege  G., Helland, Åslaug, Rye, Inga  H., Borresen-Dale, Anne -Lise, Maruyama, Reo, van Oudenaarden, Alexander, Dowsett, Mitchell, Jones, Robin  L., Reis-Filho, Jorge, Gascon, Pere, Gönen, Mithat, Michor, Franziska, and Polyak, Kornelia. Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity. United States: N. p., 2014. Web. doi:10.1016/j.celrep.2013.12.041.
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Almendro, Vanessa, Cheng, Yu -Kang, Randles, Amanda, Itzkovitz, Shalev, Marusyk, Andriy, Ametller, Elisabet, Gonzalez-Farre, Xavier, Muñoz, Montse, Russnes, Hege  G., Helland, Åslaug, Rye, Inga  H., Borresen-Dale, Anne -Lise, Maruyama, Reo, van Oudenaarden, Alexander, Dowsett, Mitchell, Jones, Robin  L., Reis-Filho, Jorge, Gascon, Pere, Gönen, Mithat, Michor, Franziska, & Polyak, Kornelia. Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity. United States. https://doi.org/10.1016/j.celrep.2013.12.041
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Almendro, Vanessa, Cheng, Yu -Kang, Randles, Amanda, Itzkovitz, Shalev, Marusyk, Andriy, Ametller, Elisabet, Gonzalez-Farre, Xavier, Muñoz, Montse, Russnes, Hege  G., Helland, Åslaug, Rye, Inga  H., Borresen-Dale, Anne -Lise, Maruyama, Reo, van Oudenaarden, Alexander, Dowsett, Mitchell, Jones, Robin  L., Reis-Filho, Jorge, Gascon, Pere, Gönen, Mithat, Michor, Franziska, and Polyak, Kornelia. Sat . "Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity". United States. https://doi.org/10.1016/j.celrep.2013.12.041. https://www.osti.gov/servlets/purl/1201672.
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@article{osti_1201672,
title = {Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity},
author = {Almendro, Vanessa and Cheng, Yu -Kang and Randles, Amanda and Itzkovitz, Shalev and Marusyk, Andriy and Ametller, Elisabet and Gonzalez-Farre, Xavier and Muñoz, Montse and Russnes, Hege  G. and Helland, Åslaug and Rye, Inga  H. and Borresen-Dale, Anne -Lise and Maruyama, Reo and van Oudenaarden, Alexander and Dowsett, Mitchell and Jones, Robin  L. and Reis-Filho, Jorge and Gascon, Pere and Gönen, Mithat and Michor, Franziska and Polyak, Kornelia},
abstractNote = {Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and post-treatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution.},
doi = {10.1016/j.celrep.2013.12.041},
journal = {Cell Reports},
number = 3,
volume = 6,
place = {United States},
year = {Sat Feb 01 00:00:00 EST 2014},
month = {Sat Feb 01 00:00:00 EST 2014}
}
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    An implantable microdevice to perform high-throughput in vivo drug sensitivity testing in tumors
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    The evolution of tumour phylogenetics: principles and practice
    journal, February 2017

    • Schwartz, Russell; Schäffer, Alejandro A.
    • Nature Reviews Genetics, Vol. 18, Issue 4
    • DOI: 10.1038/nrg.2016.170

    Molecular characterization and targeted therapeutic approaches in breast cancer
    journal, April 2015

    Translating neoadjuvant therapy into survival benefits: one size does not fit all
    journal, March 2016

    • De Mattos-Arruda, Leticia; Shen, Ronglai; Reis-Filho, Jorge S.
    • Nature Reviews Clinical Oncology, Vol. 13, Issue 9
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    Biology of lung cancer: genetic mutation, epithelial-mesenchymal transition, and cancer stem cells
    journal, July 2016

    Cancer systems biology: embracing complexity to develop better anticancer therapeutic strategies
    journal, September 2014

    Genome evolution in ductal carcinoma in situ : invasion of the clones: DCIS genome evolution
    journal, November 2016

    • Casasent, Anna K.; Edgerton, Mary; Navin, Nicholas E.
    • The Journal of Pathology, Vol. 241, Issue 2
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    Heterogeneity in Malignant Pleural Mesothelioma
    journal, May 2018

    • Oehl, Kathrin; Vrugt, Bart; Opitz, Isabelle
    • International Journal of Molecular Sciences, Vol. 19, Issue 6
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    Minimal functional driver gene heterogeneity among untreated metastases
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    • Reiter, Johannes G.; Makohon-Moore, Alvin P.; Gerold, Jeffrey M.
    • Science, Vol. 361, Issue 6406
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    The dynamic control of signal transduction networks in cancer cells
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    • Kolch, Walter; Halasz, Melinda; Granovskaya, Marina
    • Nature Reviews Cancer, Vol. 15, Issue 9
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    In situ single-cell analysis identifies heterogeneity for PIK3CA mutation and HER2 amplification in HER2-positive breast cancer
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    • Janiszewska, Michalina; Liu, Lin; Almendro, Vanessa
    • Nature Genetics, Vol. 47, Issue 10
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    Spatially resolved transcriptomics and beyond
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    • Crosetto, Nicola; Bienko, Magda; van Oudenaarden, Alexander
    • Nature Reviews Genetics, Vol. 16, Issue 1
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    Leveraging single cell RNA sequencing experiments to model intra-tumor heterogeneity
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    • Ferrall-Fairbanks, Meghan C.; Ball, Markus; Padron, Eric
    • JCO Clinical Cancer Informatics
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    Modeling differentiation-state transitions linked to therapeutic escape in triple-negative breast cancer
    journal, March 2019

    Computational Cancer Biology: An Evolutionary Perspective
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    An emerging allee effect is critical for tumor initiation and persistence
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    • Böttger, Katrin; Hatzikirou, Haralambos; Voss-Böhme, Anja
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    Cancer Evolution: Mathematical Models and Computational Inference
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    Heterogeneity in Malignant Pleural Mesothelioma
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    Clinical significance of intratumor heterogeneity for gynecological carcinoma
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    Mitochondrial levels determine variability in cell death by modulating apoptotic gene expression
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    • Márquez-Jurado, Silvia; Díaz-Colunga, Juan; das Neves, Ricardo Pires
    • Nature Communications, Vol. 9, Issue 1
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    Phase II study of ruxolitinib, a selective JAK1/2 inhibitor, in patients with metastatic triple-negative breast cancer
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    Clinical implications of changes in the diversity of c-MYC copy number variation after neoadjuvant chemotherapy in breast cancer
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    A pan-cancer signature of neutral tumor evolution
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    • Sottoriva, Andrea; Graham, Trevor A.
    • Nature Genetics
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    Reduction of LOXL2-mediated H3K4 oxidation increases chromatin accessibility and promotes chemosensitivity of triple-negative breast cancer cells
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    • Cebria-Costa, J. P.; Pascual-Reguant, L.; Gonzalez-Perez, A.
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    Statistical measures of transcriptional diversity capture genomic heterogeneity of cancer
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    Breast cancer intra-tumor heterogeneity
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    Cathepsin K induces platelet dysfunction and affects cell signaling in breast cancer - molecularly distinct behavior of cathepsin K in breast cancer
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    • Andrade, Sheila Siqueira; Gouvea, Iuri Estrada; Silva, Mariana Cristina C.
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    The impact of pharmacokinetic gene profiles across human cancers
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    • BMC Cancer, Vol. 18, Issue 1
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    Intra-tumor heterogeneity from a cancer stem cell perspective
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    Molecular characterization and targeted therapeutic approaches in breast cancer
    journal, April 2015

    GoIFISH: a system for the quantification of single cell heterogeneity from IFISH images
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    Cancer genomics: one cell at a time
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    Leveraging Single-Cell RNA Sequencing Experiments to Model Intratumor Heterogeneity
    journal, December 2019

    • Ferrall-Fairbanks, Meghan C.; Ball, Markus; Padron, Eric
    • JCO Clinical Cancer Informatics, Issue 3
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    Modeling differentiation-state transitions linked to therapeutic escape in triple-negative breast cancer
    journal, March 2019

    Addressing intra-tumoral heterogeneity and therapy resistance
    journal, September 2016

    Functional Optical Imaging of Primary Human Tumor Organoids: Development of a Personalized Drug Screen
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    • Walsh, Alex J.; Cook, Rebecca S.; Skala, Melissa C.
    • Journal of Nuclear Medicine, Vol. 58, Issue 9
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    Quantitative Spatial Analysis of Metabolic Heterogeneity Across in vivo and in vitro Tumor Models
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    • Heaster, Tiffany M.; Landman, Bennett A.; Skala, Melissa C.
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    Using Pharmacogenomic Databases for Discovering Patient-Target Genes and Small Molecule Candidates to Cancer Therapy
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    • Belizário, José E.; Sangiuliano, Beatriz A.; Perez-Sosa, Marcela
    • Frontiers in Pharmacology, Vol. 7
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    Host-Microbiome Interaction and Cancer: Potential Application in Precision Medicine
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    • Contreras, Alejandra V.; Cocom-Chan, Benjamin; Hernandez-Montes, Georgina
    • Frontiers in Physiology, Vol. 7
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    Dynamic Targeting in Cancer Treatment
    journal, February 2019

    Heterogeneity in Malignant Pleural Mesothelioma
    journal, May 2018

    • Oehl, Kathrin; Vrugt, Bart; Opitz, Isabelle
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    • DOI: 10.3390/ijms19061603

    Contribution of Epithelial Plasticity to Therapy Resistance
    journal, May 2019

    • Santamaría, Patricia G.; Moreno-Bueno, Gema; Cano, Amparo
    • Journal of Clinical Medicine, Vol. 8, Issue 5
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    BitPhylogeny: a probabilistic framework for reconstructing intra-tumor phylogenies
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    Computational Cancer Biology: An Evolutionary Perspective
    text, January 2016

    In silico analysis of DNA re-replication across a complete genome reveals cell-to-cell heterogeneity and genome plasticity
    text, January 2021

    Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights
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    Simulated Ablation for Detection of Cells Impacting Paracrine Signalling in Histology Analysis
    preprint, January 2017

    An emerging allee effect is critical for tumor initiation and persistence
    text, January 2015

    • Böttger, Katrin; Hatzikirou, Haralambos; Voss-Böhme, Anja
    • Public Library of Science (PLoS)
    • DOI: 10.5167/uzh-189902
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