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Intratumor Heterogeneity Affects Gene Expression Profile Test Prognostic Risk Stratification in Early Breast Cancer.

ABSTRACT: To examine the effect of intratumor heterogeneity (ITH) on detection of genes within gene expression panels (GEPs) and the subsequent ability to predict prognostic risk.Multiplexed barcoded RNA analysis was used to measure the expression of 141 genes from five GEPs (Oncotype Dx, MammaPrint, PAM50, EndoPredict, and Breast Cancer Index) in breast cancer tissue sections and tumor-rich cores from 71 estrogen receptor (ER)-positive node-negative tumors, on which clinical Oncotype Dx testing was previously performed. If the tumor had foci of high Ki67 (n = 26), low/negative progesterone receptor (PR; n = 13), or both (n = 5), additional cores were obtained. In total, 181 samples were processed. Oncotype Dx recurrence scores were calculated from NanoString nCounter gene expression data.Hierarchical clustering using all GEP genes showed that majority (61 of 71) of tumor samples clustered by patient, indicating greater interpatient heterogeneity (IPH) than ITH. We found a strikingly high correlation between Oncotype Dx recurrence scores obtained from whole sections versus tumor-rich cores (r = 0.94). However, high Ki67 and low PR cores had slightly higher but not statistically significant recurrence scores. For 18 of 71 (25%) patients, scores were divergent between sections and cores and crossed the boundaries for low, intermediate, and high risk.Our study indicates that in patients with highly heterogeneous tumors, GEP recurrence scores from a single core could under- or overestimate prognostic risk. Hence, it may be a useful strategy to assess multiple samples (both representative and atypical cores) to fully account for the ITH-driven variation in risk prediction. Clin Cancer Res; 22(21); 5362-9. ©2016 AACR.

SUBMITTER: Gyanchandani R

PROVIDER: S-EPMC5093028 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature

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Intratumor Heterogeneity Affects Gene Expression Profile Test Prognostic Risk Stratification in Early Breast Cancer.

Gyanchandani Rekha R Lin Yan Y Lin Hui-Min HM Cooper Kristine K Normolle Daniel P DP Brufsky Adam A Fastuca Michael M Crosson Whitney W Oesterreich Steffi S Davidson Nancy E NE Bhargava Rohit R Dabbs David J DJ Lee Adrian V AV

Clinical cancer research : an official journal of the American Association for Cancer Research 20160516 21

<h4>Purpose</h4>To examine the effect of intratumor heterogeneity (ITH) on detection of genes within gene expression panels (GEPs) and the subsequent ability to predict prognostic risk.<h4>Experimental design</h4>Multiplexed barcoded RNA analysis was used to measure the expression of 141 genes from five GEPs (Oncotype Dx, MammaPrint, PAM50, EndoPredict, and Breast Cancer Index) in breast cancer tissue sections and tumor-rich cores from 71 estrogen receptor (ER)-positive node-negative tumors, on ...[more]

PMID: 27185370

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Project description:Purpose The substratification of high-risk neuroblastoma is challenging, and new predictive imaging biomarkers are warranted for better patient selection. The aim of the study was to evaluate the prognostic role of PET-based intratumor heterogeneity and its potential ability to improve risk stratification in neuroblastoma. Methods Pretreatment 18F-FDG PET/CT scans from 112 consecutive children with newly diagnosed neuroblastoma were retrospectively analyzed. The primary tumor was segmented in the PET images. SUVs, volumetric parameters including metabolic tumor volume (MTV) and total lesion glycolysis (TLG), and texture features were extracted. After the exclusion of imaging features with poor and moderate reproducibility, the relationships between the imaging indices and clinicopathological factors, as well as event-free survival (EFS), were assessed. Results The median follow-up duration was 33 months. Multivariate analysis showed that PET-based intratumor heterogeneity outperformed clinicopathological features, including age, stage, and MYCN, and remained the most robust independent predictor for EFS [training set, hazard ratio (HR): 6.4, 95% CI: 3.1–13.2, p < 0.001; test set, HR: 5.0, 95% CI: 1.8–13.6, p = 0.002]. Within the clinical high-risk group, patients with a high metabolic heterogeneity showed significantly poorer outcomes (HR: 3.3, 95% CI: 1.6–6.8, p = 0.002 in the training set; HR: 4.4, 95% CI: 1.5–12.9, p = 0.008 in the test set) compared to those with relatively homogeneous tumors. Furthermore, intratumor heterogeneity outran the volumetric indices (MTVs and TLGs) and yielded the best performance of distinguishing high-risk patients with different outcomes with a 3-year EFS of 6% vs. 47% (p = 0.001) in the training set and 9% vs. 51% (p = 0.004) in the test set. Conclusion PET-based intratumor heterogeneity was a strong independent prognostic factor in neuroblastoma. In the clinical high-risk group, intratumor heterogeneity further stratified patients with distinct outcomes.

Project description:BackgroundPolygenic risk scores (PRS) could potentially improve breast cancer screening recommendations. Before a PRS can be considered for implementation, it needs rigorous evaluation, using performance measures that can inform about its future clinical value.ObjectivesTo evaluate the prognostic performance of a regression model with a previously developed, prevalence-based PRS and age as predictors for breast cancer incidence in women from the Estonian biobank (EstBB) cohort; to compare it to the performance of a model including age only.MethodsWe analyzed data on 30,312 women from the EstBB cohort. They entered the cohort between 2002 and 2011, were between 20 and 89 years, without a history of breast cancer, and with full 5-year follow-up by 2015. We examined PRS and other potential risk factors as possible predictors in Cox regression models for breast cancer incidence. With 10-fold cross-validation we estimated 3- and 5-year breast cancer incidence predicted by age alone and by PRS plus age, fitting models on 90% of the data. Calibration, discrimination, and reclassification were calculated on the left-out folds to express prognostic performance.ResultsA total of 101 (3.33‰) and 185 (6.1‰) incident breast cancers were observed within 3 and 5 years, respectively. For women in a defined screening age of 50-62 years, the ratio of observed vs PRS-age modelled 3-year incidence was 0.86 for women in the 75-85% PRS-group, 1.34 for the 85-95% PRS-group, and 1.41 for the top 5% PRS-group. For 5-year incidence, this was respectively 0.94, 1.15, and 1.08. Yet the number of breast cancer events was relatively low in each PRS-subgroup. For all women, the model's AUC was 0.720 (95% CI: 0.675-0.765) for 3-year and 0.704 (95% CI: 0.670-0.737) for 5-year follow-up, respectively, just 0.022 and 0.023 higher than for the model with age alone. Using a 1% risk prediction threshold, the 3-year NRI for the PRS-age model was 0.09, and 0.05 for 5 years.ConclusionThe model including PRS had modest incremental performance over one based on age only. A larger, independent study is needed to assess whether and how the PRS can meaningfully contribute to age, for developing more efficient screening strategies.

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Intratumor Heterogeneity Affects Gene Expression Profile Test Prognostic Risk Stratification in Early Breast Cancer.

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Intratumor Heterogeneity Affects Gene Expression Profile Test Prognostic Risk Stratification in Early Breast Cancer.

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