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Multi-level gene expression signatures, but not binary, outperform Ki67 for the long term prognostication of breast cancer patients.

ABSTRACT: Proliferation-related gene signatures have been proposed to aid breast cancer management by providing reproducible prognostic and predictive information on a patient-by-patient basis. It is unclear however, whether a less demanding assessment of cell division rate (as determined in clinical setting by expression of Ki67) can function in place of gene profiling. We investigated agreement between literature-, distribution-based, as well as signature-derived values for Ki67, relative to the genomic grade index (GGI), 70-gene signature, p53 signature, recurrence score (RS), and the molecular subtype models of Sorlie, Hu, and Parker in representative sets of 253 and 159 breast cancers with a median follow-up of 13 and 14.5 years, respectively. The relevance for breast cancer specific survival was also addressed in uni- and bivariate Cox models. Taking both cohorts into account, our broad approach identified ROC optimized Ki67 cutoffs in the range of 8-28%. With optimum signature-reproducing cutoffs, similarity in classification of individual tumors was higher for binary signatures (72-85%), than multi-level signatures (67-73%). Consistent with strong agreement, no prognostic superiority was noted for either Ki67 or the binary GGI, 70-gene and p53 signatures in the Uppsala dataset by bivariate analyses. In contrast, Ki67-independent prognostic capacity could be demonstrated for RS and molecular subtypes according to Sorlie, Hu and Parker in both datasets. Our results show that the added prognostic value of binary proliferation-related gene signatures is limited for Ki67-assessed breast cancers. More complex, multi-level descriptions have a greater potential in short- and long-term prognostication for biologically relevant breast cancer subgroups.

SUBMITTER: Tobin NP

PROVIDER: S-EPMC5528643 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Multi-level gene expression signatures, but not binary, outperform Ki67 for the long term prognostication of breast cancer patients.

Tobin Nicholas P NP Lindström Linda S LS Carlson Joseph W JW Bjöhle Judith J Bergh Jonas J Wennmalm Kristian K

Molecular oncology 20140228 3

Proliferation-related gene signatures have been proposed to aid breast cancer management by providing reproducible prognostic and predictive information on a patient-by-patient basis. It is unclear however, whether a less demanding assessment of cell division rate (as determined in clinical setting by expression of Ki67) can function in place of gene profiling. We investigated agreement between literature-, distribution-based, as well as signature-derived values for Ki67, relative to the genomic ...[more]

PMID: 24630985

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Project description:ObjectiveThe concept of the 'self-fulfilling prophecy' is well established in intracerebral haemorrhage (ICH). The ability to improve prognostication and prediction of long-term outcomes during the first days of hospitalisation is important in guiding conversations around goals of care. We previously demonstrated that incorporating delayed imaging into various prognostication scores for ICH improves the predictive accuracy of 90-day mortality. However, delayed prognostication scores have not been used to predict long-term functional outcomes beyond 90 days.Design, setting and participantsWe analysed data from the ICH Deferoxamine trial to see if delaying the use of prognostication scores to 96 hours after ICH onset will improve performance to predict outcomes at 180 days. 276 patients were included.Interventions and measurementsWe calculated the original ICH score (oICH), modified-ICH score (MICH), max-ICH score and the FUNC score on presentation (baseline), and on day 4 (delayed). Outcomes assessed were mortality and poor functional outcome in survivors (defined as modified Rankin Scale of 4-5) at 180 days. We generated receiver operating characteristic curves, and measured the area under the curve values (AUC) for mortality and functional outcome. We compared baseline and delayed AUCs with non-parametric methods.ResultsAt 180 days, 21 of 276 (7.6%) died. Out of the survivors, 54 of 255 had poor functional outcome (21.2%). The oICH, MICH and max-ICH performed significantly better at predicting 180-day mortality when calculated 4 days later compared with their baseline equivalents ((0.74 vs 0.83, p=0.005), (0.73 vs 0.80, p=0.036), (0.74 vs 0.83, p=0.008), respectively). The delayed calculation of these scores did not significantly improve our accuracy for predicting poor functional outcomes.ConclusionDelaying the calculation of prognostication scores in acute ICH until day 4 improved prediction of 6-month mortality but not functional outcomes.Trial registration numberClinicalTrials.gov Registry (NCT02175225).

Dataset Information

Multi-level gene expression signatures, but not binary, outperform Ki67 for the long term prognostication of breast cancer patients.

Publications

Multi-level gene expression signatures, but not binary, outperform Ki67 for the long term prognostication of breast cancer patients.

Similar Datasets

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