title: Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology-Genomic Integration Analysis.
abstract: BACKGROUND
  The intra-tumor diversity of cancer cells is under intense investigation; however, little is known about the heterogeneity of the tumor microenvironment that is key to cancer progression and evolution. We aimed to assess the degree of microenvironmental heterogeneity in breast cancer and correlate this with genomic and clinical parameters.
  
  
  RESULTS
  We developed a quantitative measure of microenvironmental heterogeneity along three spatial dimensions (3-D) in solid tumors, termed the tumor ecosystem diversity index (EDI), using fully automated histology image analysis coupled with statistical measures commonly used in ecology. This measure was compared with disease-specific survival, key mutations, genome-wide copy number, and expression profiling data in a retrospective study of 510 breast cancer patients as a test set and 516 breast cancer patients as an independent validation set. In high-grade (grade 3) breast cancers, we uncovered a striking link between high microenvironmental heterogeneity measured by EDI and a poor prognosis that cannot be explained by tumor size, genomics, or any other data types. However, this association was not observed in low-grade (grade 1 and 2) breast cancers. The prognostic value of EDI was superior to known prognostic factors and was enhanced with the addition of TP53 mutation status (multivariate analysis test set, p = 9 × 10-4, hazard ratio = 1.47, 95% CI 1.17-1.84; validation set, p = 0.0011, hazard ratio = 1.78, 95% CI 1.26-2.52). Integration with genome-wide profiling data identified losses of specific genes on 4p14 and 5q13 that were enriched in grade 3 tumors with high microenvironmental diversity that also substratified patients into poor prognostic groups. Limitations of this study include the number of cell types included in the model, that EDI has prognostic value only in grade 3 tumors, and that our spatial heterogeneity measure was dependent on spatial scale and tumor size.
  
  
  CONCLUSIONS
  To our knowledge, this is the first study to couple unbiased measures of microenvironmental heterogeneity with genomic alterations to predict breast cancer clinical outcome. We propose a clinically relevant role of microenvironmental heterogeneity for advanced breast tumors, and highlight that ecological statistics can be translated into medical advances for identifying a new type of biomarker and, furthermore, for understanding the synergistic interplay of microenvironmental heterogeneity with genomic alterations in cancer cells.
authors.affiliation: Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, United Kingdom.|Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom.
authors.forename: Rachael
authors.initials: R
authors.lastname: Natrajan
authors.affiliation: Division of Cancer Biology, The Institute of Cancer Research, London, United Kingdom.
authors.forename: Heba
authors.initials: H
authors.lastname: Sailem
authors.affiliation: Division of Cancer Biology, The Institute of Cancer Research, London, United Kingdom.
authors.forename: Faraz K
authors.initials: FK
authors.lastname: Mardakheh
authors.affiliation: Division of Cancer Biology, The Institute of Cancer Research, London, United Kingdom.
authors.forename: Mar
authors.initials: M
authors.lastname: Arias Garcia
authors.affiliation: Division of Cancer Biology, The Institute of Cancer Research, London, United Kingdom.
authors.forename: Christopher J
authors.initials: CJ
authors.lastname: Tape
authors.affiliation: Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, United Kingdom.|Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom.|Centre for Molecular Pathology, Royal Marsden Hospital, London, United Kingdom.|Academic Department of Biochemistry, Royal Marsden Hospital, London, United Kingdom.
authors.forename: Mitch
authors.initials: M
authors.lastname: Dowsett
authors.affiliation: Division of Cancer Biology, The Institute of Cancer Research, London, United Kingdom.
authors.forename: Chris
authors.initials: C
authors.lastname: Bakal
authors.affiliation: Division of Molecular Pathology, The Institute of Cancer Research, London, United Kingdom.|Centre for Molecular Pathology, Royal Marsden Hospital, London, United Kingdom.|Centre for Evolution and Cancer, The Institute of Cancer Research, London, United Kingdom.
authors.forename: Yinyin
authors.initials: Y
authors.lastname: Yuan
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000235:genetics* / Q000378:metabolism; D001943:Breast Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000473:pathology; D004273:DNA, Neoplasm / Q000235:genetics*; D018450:Disease Progression; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D023281:Genomics / Q000379:methods*; D006801:Humans; D008875:Middle Aged; D009367:Neoplasm Staging; D011379:Prognosis; D012189:Retrospective Studies; D055815:Young Adult
chemical_list: D014408:Biomarkers, Tumor; D004273:DNA, Neoplasm