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Cross comparison and prognostic assessment of breast cancer multigene signatures in a large population-based contemporary clinical series

Vallon-Christersson, Johan LU orcid ; Häkkinen, Jari LU orcid ; Hegardt, Cecilia LU ; Saal, Lao LU orcid ; Larsson, Christer LU ; Ehinger, Anna LU orcid ; Lindman, H ; Olofsson, Helena ; Sjoblom, Tobias and Wärnberg, Fredrik , et al. (2019) In Scientific Reports 9.
Abstract
Multigene expression signatures provide a molecular subdivision of early breast cancer associated with patient outcome. A gap remains in the validation of such signatures in clinical treatment groups of patients within population-based cohorts of unselected primary breast cancer representing contemporary disease stages and current treatments. A cohort of 3520 resectable breast cancers with RNA sequencing data included in the population-based SCAN-B initiative (ClinicalTrials.gov ID NCT02306096) were selected from a healthcare background population of 8587 patients diagnosed within the years 2010-2015. RNA profiles were classified according to 19 reported gene signatures including both gene expression subtypes (e.g. PAM50, IC10, CIT) and... (More)
Multigene expression signatures provide a molecular subdivision of early breast cancer associated with patient outcome. A gap remains in the validation of such signatures in clinical treatment groups of patients within population-based cohorts of unselected primary breast cancer representing contemporary disease stages and current treatments. A cohort of 3520 resectable breast cancers with RNA sequencing data included in the population-based SCAN-B initiative (ClinicalTrials.gov ID NCT02306096) were selected from a healthcare background population of 8587 patients diagnosed within the years 2010-2015. RNA profiles were classified according to 19 reported gene signatures including both gene expression subtypes (e.g. PAM50, IC10, CIT) and risk predictors (e.g. Oncotype DX, 70-gene, ROR). Classifications were analyzed in nine adjuvant clinical assessment groups: TNBC-ACT (adjuvant chemotherapy, n = 239), TNBC-untreated (n = 82), HER2+/ER- with anti-HER2+ ACT treatment (n = 110), HER2+/ER+ with anti-HER2 + ACT + endocrine treatment (n = 239), ER+/HER2-/LN- with endocrine treatment (n = 1113), ER+/HER2-/LN- with endocrine + ACT treatment (n = 243), ER+/HER2-/LN+ with endocrine treatment (n = 423), ER+/HER2-/LN+ with endocrine + ACT treatment (n = 433), and ER+/HER2-/LN- untreated (n = 200). Gene signature classification (e.g., proportion low-, high-risk) was generally well aligned with stratification based on current immunohistochemistry-based clinical practice. Most signatures did not provide any further risk stratification in TNBC and HER2+/ER- disease. Risk classifier agreement (low-, medium/intermediate-, high-risk groups) in ER+ assessment groups was on average 50-60% with occasional pair-wise comparisons having <30% agreement. Disregarding the intermediate-risk groups, the exact agreement between low- and high-risk groups was on average ~80-95%, for risk prediction signatures across all assessment groups. Outcome analyses were restricted to assessment groups of TNBC-ACT and endocrine treated ER+/HER2-/LN- and ER+/HER2-/LN+ cases. For ER+/HER2- disease, gene signatures appear to contribute additional prognostic value even at a relatively short follow-up time. Less apparent prognostic value was observed in the other groups for the tested signatures. The current study supports the usage of gene expression signatures in specific clinical treatment groups within population-based breast cancer. It also stresses the need of further development to reach higher consensus in individual patient classifications, especially for intermediate-risk patients, and the targeting of patients where current gene signatures and prognostic variables provide little support in clinical decision-making. (Less)
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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Scientific Reports
volume
9
article number
12184
publisher
Nature Publishing Group
external identifiers
  • scopus:85071073365
  • pmid:31434940
ISSN
2045-2322
DOI
10.1038/s41598-019-48570-x
project
Sweden Cancerome Analysis Network - Breast (SCAN-B): a large-scale multicenter infrastructure towards implementation of breast cancer genomic analyses in the clinical routine
Genomisk karakterisering av trippelnegativ bröstcancer (TNBC)
language
English
LU publication?
yes
id
ba6c0a32-c4e1-468b-8318-8804d5c083c9
date added to LUP
2019-08-23 13:08:54
date last changed
2022-05-11 20:43:03
@article{ba6c0a32-c4e1-468b-8318-8804d5c083c9,
  abstract     = {{Multigene expression signatures provide a molecular subdivision of early breast cancer associated with patient outcome. A gap remains in the validation of such signatures in clinical treatment groups of patients within population-based cohorts of unselected primary breast cancer representing contemporary disease stages and current treatments. A cohort of 3520 resectable breast cancers with RNA sequencing data included in the population-based SCAN-B initiative (ClinicalTrials.gov ID NCT02306096) were selected from a healthcare background population of 8587 patients diagnosed within the years 2010-2015. RNA profiles were classified according to 19 reported gene signatures including both gene expression subtypes (e.g. PAM50, IC10, CIT) and risk predictors (e.g. Oncotype DX, 70-gene, ROR). Classifications were analyzed in nine adjuvant clinical assessment groups: TNBC-ACT (adjuvant chemotherapy, n = 239), TNBC-untreated (n = 82), HER2+/ER- with anti-HER2+ ACT treatment (n = 110), HER2+/ER+ with anti-HER2 + ACT + endocrine treatment (n = 239), ER+/HER2-/LN- with endocrine treatment (n = 1113), ER+/HER2-/LN- with endocrine + ACT treatment (n = 243), ER+/HER2-/LN+ with endocrine treatment (n = 423), ER+/HER2-/LN+ with endocrine + ACT treatment (n = 433), and ER+/HER2-/LN- untreated (n = 200). Gene signature classification (e.g., proportion low-, high-risk) was generally well aligned with stratification based on current immunohistochemistry-based clinical practice. Most signatures did not provide any further risk stratification in TNBC and HER2+/ER- disease. Risk classifier agreement (low-, medium/intermediate-, high-risk groups) in ER+ assessment groups was on average 50-60% with occasional pair-wise comparisons having &lt;30% agreement. Disregarding the intermediate-risk groups, the exact agreement between low- and high-risk groups was on average ~80-95%, for risk prediction signatures across all assessment groups. Outcome analyses were restricted to assessment groups of TNBC-ACT and endocrine treated ER+/HER2-/LN- and ER+/HER2-/LN+ cases. For ER+/HER2- disease, gene signatures appear to contribute additional prognostic value even at a relatively short follow-up time. Less apparent prognostic value was observed in the other groups for the tested signatures. The current study supports the usage of gene expression signatures in specific clinical treatment groups within population-based breast cancer. It also stresses the need of further development to reach higher consensus in individual patient classifications, especially for intermediate-risk patients, and the targeting of patients where current gene signatures and prognostic variables provide little support in clinical decision-making.}},
  author       = {{Vallon-Christersson, Johan and Häkkinen, Jari and Hegardt, Cecilia and Saal, Lao and Larsson, Christer and Ehinger, Anna and Lindman, H and Olofsson, Helena and Sjoblom, Tobias and Wärnberg, Fredrik and Rydén, Lisa and Loman, Niklas and Malmberg, Martin and Borg, Åke and Staaf, Johan}},
  issn         = {{2045-2322}},
  language     = {{eng}},
  month        = {{08}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Scientific Reports}},
  title        = {{Cross comparison and prognostic assessment of breast cancer multigene signatures in a large population-based contemporary clinical series}},
  url          = {{http://dx.doi.org/10.1038/s41598-019-48570-x}},
  doi          = {{10.1038/s41598-019-48570-x}},
  volume       = {{9}},
  year         = {{2019}},
}